Name: Level 7 Diploma in AWS Cloud Practitioner - QLS Endorsed
Price: 105 GBP
Availability: InStock

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          <p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);">The Complete Python Course - Beginner to Expert is an extensive learning program designed to take participants from novice to proficient Python programmers. Throughout the course, learners will embark on a comprehensive journey covering fundamental Python concepts and gradually progressing to advanced topics.</span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);">The course begins with an introduction to Python programming, providing an overview of its syntax, data types, and basic operations. Participants will gain a solid understanding of Python fundamentals, including variables, operators, and control flow structures.</span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);">As the course progresses, learners will delve deeper into advanced Python concepts, such as error handling, functions, and object-oriented programming. They will explore the intricacies of Python libraries, including NumPy and Pandas, for data manipulation and analysis.</span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);">Furthermore, participants will receive invaluable guidance on launching a successful career in Python, including tips on freelancing, networking, and building a strong professional brand. By the end of the course, learners will be equipped with the knowledge and skills to pursue various career opportunities in Python development, data analysis, machine learning, and more.</span></p><h2 dir="ltr" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Learning Outcome of &nbsp;Complete Python Course - Beginner to Expert</span></h2><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Gain a thorough grasp of Python programming from beginner to advanced levels.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Learn Python syntax, covering comments, line structure, and indentation.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Understand basic data types like strings, integers, floats, and booleans, and how to manipulate them.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Explore Python operators, including comparison, arithmetic, and logical operators.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Delve into advanced data types such as sets, lists, tuples, and dictionaries.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Master control flow structures like conditional statements and loops.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Develop proficiency in defining and using functions, understanding variable scope, and using docstrings.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Learn user input and error handling techniques, including syntax errors and exceptions.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Explore advanced topics like lambda functions, iterators, generators, and functional programming.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Discover scripting and libraries usage, including IDEs, text editors, and importing scripts.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Explore NumPy for numerical computing, including arrays and data manipulation.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Master data manipulation with Pandas, including dealing with missing values.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Get an introduction to object-oriented programming (OOP) concepts.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Explore advanced OOP topics like decorators, inheritance, and class methods.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Receive guidance on starting a career in Python, including freelancing and networking.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Key Features of the Course</span></h2><ul fr-original-style="" style="box-sizing: border-box;"><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">A CPD certificate that is recognised worldwide.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">A great online learning experience.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Interesting and unique online materials and activities.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Expert guidance and support from the field leaders.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Access to the study resources anytime you want.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Friendly and helpful customer service and admin support by email, phone, and chat from Monday through Friday.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Get a year-long access to the course.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Who is this course for</span></h2><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">This &nbsp;Complete Python Course - Beginner to Expert Course is suitable for -</span></p></div><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Individuals new to programming</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Students seeking Python proficiency</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Professionals transitioning to Python</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Anyone aiming for expertise in Python</li></ul><h2 dir="ltr" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Requirements</span></h2><div id="course-pricing" fr-original-style="" style="box-sizing: border-box;"><ul fr-original-style="" style="box-sizing: border-box;"><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Open to all interested in Python.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">&nbsp;No prerequisites; suitable for individuals from any academic background.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Accessible course materials from any internet-enabled device.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">CPD Certificate from Course Gate</span></h2><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for &pound;9 and the hard copy for &pound;15. Also, you can order both PDF and hardcopy certificates for &pound;22.</span></p><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Career path</span></h2></div><div fr-original-style="" style="box-sizing: border-box;"><div fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><div fr-original-style="" style="box-sizing: border-box;"><div fr-original-style="" style="box-sizing: border-box;"><div fr-original-style="" style="box-sizing: border-box;"><div fr-original-style="" style="box-sizing: border-box;"><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Python Developer</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Analyst</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Software Engineer</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Machine Learning Engineer</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Web Developer</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Scientist</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Automation Engineer</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Cybersecurity Analyst</li></ul>
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Course Gate

Python Scripting

Unlock your potential in Python programming with our Complete Python Course - Beginner to Expert! From mastering syntax to advanced data analysis, machine learning, and web development, this comprehensive course equips you with essential programming skills. Start your journey today and become a proficient Python developer!

Complete Python Course - Beginner to Expert

General Admission

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p>The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful.</p>Overview<p>Overview of data science and machine learning at scale<br />Overview of the Hadoop ecosystem<br />Working with HDFS data and Hive tables using Hue<br />Introduction to Cloudera Data Science Workbench<br />Overview of Apache Spark 2<br />Reading and writing data<br />Inspecting data quality<br />Cleansing and transforming data<br />Summarizing and grouping data<br />Combining, splitting, and reshaping data<br />Exploring data<br />Configuring, monitoring, and troubleshooting Spark applications<br />Overview of machine learning in Spark MLlib<br />Extracting, transforming, and selecting features<br />Building and evaluating regression models<br />Building and evaluating classification models<br />Building and evaluating clustering models<br />Cross-validating models and tuning hyperparameters<br />Building machine learning pipelines<br />Deploying machine learning models<br />Spark, Spark SQL, and Spark MLlib<br />PySpark and sparklyr<br />Cloudera Data Science Workbench (CDSW)<br />Hue</p><p>This workshop covers data science and machine learning workflows at scale using Apache Spark 2 and other key components of the Hadoop ecosystem. The workshop emphasizes the use of data science and machine learning methods to address real-world business challenges. Using scenarios and datasets from a fictional technology company, students discover insights to support critical business decisions and develop data products to transform the business. The material is presented through a sequence of brief lectures, interactive demonstrations, extensive hands-on exercises, and discussions. The Apache Spark demonstrations and exercises are conducted in Python (with PySpark) and R (with sparklyr) using the Cloudera Data Science Workbench (CDSW) environment. The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful.</p></div><div id="course-pills-2"><h4>Overview of data science and machine learning at scale</h4><h4>Overview of the Hadoop ecosystem</h4><h4>Working with HDFS data and Hive tables using Hue</h4><h4>Introduction to Cloudera Data Science Workbench</h4><h4>Overview of Apache Spark 2</h4><h4>Reading and writing data</h4><h4>Inspecting data quality</h4><h4>Cleansing and transforming data</h4><h4>Summarizing and grouping data</h4><h4>Combining, splitting, and reshaping data</h4><h4>Exploring data</h4><h4>Configuring, monitoring, and troubleshooting Spark applications</h4><h4>Overview of machine learning in Spark MLlib</h4><h4>Extracting, transforming, and selecting features</h4><h4>Building and evauating regression models</h4><h4>Building and evaluating classification models</h4><h4>Building and evaluating clustering models</h4><h4>Cross-validating models and tuning hyperparameters</h4><h4>Building machine learning pipelines</h4><h4>Deploying machine learning models</h4></div><div id="course-pills-3"><h4>Additional course details:</h4><br /><p>Nexus Humans Cloudera Data Scientist Training training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. </p><p></p> This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. <p></p>Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.  <p></p>While we feel this is the best course for the Cloudera Data Scientist Training course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.  <p></p>Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.<p></p></div>

Nexus Human

Data Engineering

Apache Spark

Big Data Analytics

Hadoop

Data Science

Data Skills

Cloudera Data Scientist Training

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			<h2>Overview
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					<p>Mastering data science skills and expertise can open new doors of opportunities for you in a wide range of fields. Learn the fundamentals and develop a solid grasp of Python data science with the comprehensive Data Science with Python course. This course is designed to assist you in securing a valuable skill set and boosting your career.</p><p>This course will provide you with quality training on the fundamentals of data analysis with Python. From the step-by-step learning process, you will learn the techniques of setting up the system. Then the course will teach you Python data structure and functions. You will receive detailed lessons on NumPy, Matplotlib, and Pandas. Furthermore, you will develop the skills for Algorithm Evaluation Techniques, visualising datasets and much more.</p><p>After completing the course you will receive a certificate of achievement. This certificate will help you create an impressive resume. So join today!</p>					</div>
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			<h2>How will I get my certificate?</h2>		</div>
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					<p><span>You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.</span></p>					</div>
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					<p>This course Data Science with Python course is ideal for beginners in data science. It will help them develop a solid grasp of Python and help them pursue their dream career in the field of data science.</p>					</div>
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			<h2>Requirements</h2>		</div>
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					<p>The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush.</p>					</div>
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					<p>This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as</p><ul><li>Data Analyst </li><li>Data Scientist </li><li>Data Manager </li><li>Business Analyst</li></ul><p>And much more!</p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>90 sections • 90 lectures • 10:19:00 total length</p></div><div><div><div><div><div><div><div><p>•Course Overview &amp; Table of Contents: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•System and Environment preparation - Part 1: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•System and Environment preparation - Part 2: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of python - Assignment 1: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of python - Assignment 2: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of python - Functions: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of python - Data Structures: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of NumPy - NumPy Array: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of NumPy - NumPy Data: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of NumPy - NumPy Arithmetic: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of Matplotlib: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of Pandas - Part 1: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Learn Basics of Pandas - Part 2: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Understanding the CSV data file: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Load and Read CSV data file using Python Standard Library: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Load and Read CSV data file using NumPy: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Load and Read CSV data file using Pandas: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Summary - Peek, Dimensions and Data Types: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Summary - Class Distribution and Data Summary: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Summary - Explaining Correlation: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Visualization - Using Histograms: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Visualization - Using Density Plots: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Dataset Visualization - Box and Whisker Plots: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Multivariate Dataset Visualization - Correlation Plots: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Multivariate Dataset Visualization - Scatter Plots: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation (Pre-Processing) - Introduction: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Re-scaling Data - Part 1: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Re-scaling Data - Part 2: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Standardizing Data - Part 1: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Standardizing Data - Part 2: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Normalizing Data: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Preparation - Binarizing Data: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Introduction: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Recursive Feature Elimination: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Principal Component Analysis (PCA): 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Feature Selection - Feature Importance: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Techniques - Introduction: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Techniques - Train and Test Set: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Introduction: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Log Loss: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Classification Report: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - Mean Square Error: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Algorithm Evaluation Metrics - R Squared: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - Logistic Regression: 00:12:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - Naive Bayes: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - CART: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Classification Algorithm Spot Check - Support Vector Machines: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - Linear Regression: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - Ridge Regression: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - CART: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Pipelines : Data Preparation and Data Modelling: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Pipelines : Feature Selection and Data Modelling: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Performance Improvement: Ensembles - Voting: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Performance Improvement: Ensembles - Bagging: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Performance Improvement: Ensembles - Boosting: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Performance Improvement: Parameter Tuning using Grid Search: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Performance Improvement: Parameter Tuning using Random Search: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Export, Save and Load Machine Learning Models : Pickle: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Export, Save and Load Machine Learning Models : Joblib: 00:06:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Finalizing a Model - Introduction and Steps: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Resources - Data Science &amp; Machine Learning with Python: 00:00:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Apex Learning

Computing Skills

Data Science with Python

<p><strong>***24 Hour Limited Time Flash Sale***</strong></p><p><strong> </strong><strong>Software Engineering: Master Programming, Web Design &amp; Development </strong><strong>Admission Gifts </strong></p><p><strong> FREE PDF &amp; Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter</strong></p><p>Are you a professional feeling stuck in your career, struggling to keep up with the ever-changing demands of the industry? Or perhaps you're a beginner, unsure of where to start or how to break into your desired field. Whichever stage you're in, our exclusive Software Engineering: Master Programming, Web Design &amp; Development Bundle provides unique insights and tools that can help you achieve your goals.</p><p>Designed to cater to the needs of both seasoned professionals and aspiring newcomers, our Software Engineering: Master Programming, Web Design &amp; Development bundle is a comprehensive program that will equip you with the essential skills and knowledge you need to succeed. Whether you're looking to advance in your current role or embark on a new career journey, this bundle has everything you need to take your professional life to the next level.</p><p><strong>But that's not all. When you enrol in Software Engineering: Master Programming, Web Design &amp; Development Online Training, you'll receive 30 CPD-Accredited PDF Certificates, Hard Copy Certificates, and our exclusive student ID card, all absolutely free.</strong></p><p><strong>Courses Are Included In this Software Engineering: Master Programming, Web Design &amp; Development Career Bundle:</strong></p><ul><li> Course 01: Coding with Scratch</li><li> Course 02: C# Programming - Beginner to Advanced</li><li> Course 03: Python Programming Bible</li><li> Course 04: Machine Learning with Python Course</li><li> Course 05: JavaScript Fundamentals</li><li> Course 06: Refactor Javascript</li><li> Course 07: Penetration Testing with OWASP ZAP</li><li> Course 08: Advanced SAS Programming Using MacrosSQL</li><li> Course 09: How To Startup Your Own SaaS (Software As a Service) Company (SaaS Evolution)</li><li> Course 10: Three.js &amp; WebGL 3D Programming</li><li> Course 11: Stripe with C#</li><li> Course 12: C++ Development: The Complete Coding Guide</li><li> Course 13: Bootstrap - Responsive Web Design</li><li> Course 14: Masterclass Bootstrap 5 Course - Responsive Web Design</li><li> Course 15: Diploma in User Experience UI/UX Design (Advanced)</li><li> Course 16: Advanced Diploma in PHP Web Development with MySQL, GitHub &amp; Heroku</li><li> Course 17: Node JS: API Development with Swagger</li><li> Course 18: HTML Web Development Crash Course</li><li> Course 19: CSS Web Development</li><li> Course 20: .NET Core API Development</li><li> Course 21: Graphic Design Using Canva</li><li> Course 22: Basics of WordPress: Create Unlimited Websites</li><li> Course 23: The Ultimate WordPress for Beginners Step-by-Step Blueprint</li><li> Course 24: Using WordPress for Affiliate Marketing</li><li> Course 25: WordPress 5.0 for Beginners to Advanced</li><li> Course 26: WordPress and SEO Online Course</li><li> Course 27: How To Build Easy Drag &amp; Drop Landing Pages With Wordpress</li><li> Course 28: Make a Wordpress WooCommerce Amazon Affiliate Store</li><li> Course 29: Wordpress Security Mastery</li><li> Course 30: How To Build a Wordpress Membership Site With Memberpress</li></ul><p>With Software Engineering: Master Programming, Web Design &amp; Development, you'll embark on an immersive learning experience that combines interactive lessons with voice-over audio, ensuring that you can learn from anywhere in the world, at your own pace. 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Enrol in Software Engineering: Master Programming, Web Design &amp; Development today and take the first step towards achieving your goals and dreams.</p><p><strong>Why buy this Software Engineering: Master Programming, Web Design &amp; Development?</strong></p><ul><li><strong>Free CPD Accredited Certificate</strong> upon completion of Software Engineering: Master Programming, Web Design &amp; Development</li><li>Get <strong>a free student ID card</strong> with Software Engineering: Master Programming, Web Design &amp; Development</li><li><strong>Lifetime access</strong> to the Software Engineering: Master Programming, Web Design &amp; Development course materials</li><li>Get instant access to this Software Engineering: Master Programming, Web Design &amp; Development course</li><li>Learn Software Engineering: Master Programming, Web Design &amp; Development from anywhere in the world</li><li>24/7 tutor support with the Software Engineering: Master Programming, Web Design &amp; Development course.</li></ul> <p><strong>Start your learning journey straightaway with our Software Engineering: Master Programming, Web Design &amp; Development Training!</strong></p><p>Software Engineering: Master Programming, Web Design &amp; Development premium bundle consists of 30 precisely chosen courses on a wide range of topics essential for anyone looking to excel in this field. Each segment of the Software Engineering: Master Programming, Web Design &amp; Development is meticulously designed to maximise learning and engagement, blending interactive content and audio-visual modules for a truly immersive experience.</p><p><strong>Certification</strong></p><p>You have to complete the assignment given at the end of the Software Engineering: Master Programming, Web Design &amp; Development course. After passing the Software Engineering: Master Programming, Web Design &amp; Development exam You will be entitled to claim a PDF &amp; Hardcopy certificate accredited by CPD Quality standards completely free.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        300 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p><strong>This Software Engineering: Master Programming, Web Design &amp; Development course is ideal for:</strong></p><ul><li>Students seeking mastery in Software Engineering: Master Programming, Web Design &amp; Development</li><li>Professionals seeking to enhance Software Engineering: Master Programming, Web Design &amp; Development skills</li><li>Individuals looking for a Software Engineering: Master Programming, Web Design &amp; Development-related career.</li><li>Anyone passionate about Software Engineering: Master Programming, Web Design &amp; Development</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This <strong>Software Engineering: Master Programming, Web Design &amp; Development </strong>doesn't require prior experience and is suitable for diverse learners.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This <strong>Software Engineering: Master Programming, Web Design &amp; Development </strong>bundle will allow you to kickstart or take your career in the related sector to the next stage.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Digital Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Hard Copy Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p>If you are an international student, you will be required to pay an additional fee of <strong>10 GBP</strong> for international delivery, and <strong>4.99 GBP</strong> for delivery within the UK, for each certificate</p></div>

                        </div>

Academy for Health and Fitness

Software Engineering: Master Programming, Web Design & Development

School of Business and Technology London

QUALIFI Level 7 Diploma in Data Science

<p><strong>24 Hour Flash Deal **25-in-1 Level 3 Diploma in ICT Information Systems and Principles for IT Professionals Mega Bundle**</strong><br /><br /><strong> Level 3 Diploma in ICT Information Systems and Principles for IT Professionals Enrolment Gifts  **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter **</strong><br /><br />Take the initial steps toward a successful long-term career by studying the <strong>Level 3 Diploma in ICT Information Systems and Principles for IT Professionals</strong> package online with <strong>Studyhub </strong>through our online learning platform. 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Plus Studyhub's signature <strong>Forever Access</strong> is given as always, meaning these <strong>Level 3 Diploma in ICT Information Systems and Principles for IT Professionals</strong> courses are yours for as long as you want them once you enrol in this course<br /><br /><strong>This Level 3 Diploma in ICT Information Systems and Principles for IT Professionals Bundle consists the following career oriented courses:</strong></p><ul><li>Course 01: IT Skills for IT / Non - IT Professionals</li><li>Course 02: Computer Operating System and Troubleshooting</li><li>Course 03: IT Support Technician: Troubleshooting and Technical Expertise</li><li>Course 04: Computer Workstation Safety Training</li><li>Course 05: Foundations of IT Security: Protecting Digital Assets</li><li>Course 06: Cyber Security Awareness Training</li><li>Course 07: Cyber Security Incident Handling and Incident Response</li><li>Course 08: Information Governance and Data Management Training</li><li>Course 09: SQL Database Management</li><li>Course 10: Data Analytics</li><li>Course 11: Quick Data Science Approach from Scratch</li><li>Course 12: Machine Learning Basics</li><li>Course 13: Deep Learning Neural Network with R</li><li>Course 14: Cyber Security Law</li><li>Course 15: CEH: Learn Ethical Hacking From A-Z: Beginner To Expert</li><li>Course 16: Computer Networks Security from Scratch to Advanced</li><li>Course 17: CompTIA Network+ Certification (N10-007)</li><li>Course 18: Functional Skills IT/ ICT Level 2</li><li>Course 19: Internet of Things (IoT)</li><li>Course 20: Information Architecture (IA) Fundamentals for Website Design</li><li>Course 21: Learn Fundamentals of WordPress</li><li>Course 22: Digital Forensic Science: Unraveling Cybercrime Mysteries Course</li><li>Course 23: IT Administration and Networking</li><li>Course 24: Data Center Training Essentials: General Introduction</li><li>Course 25: Network Security and Risk Management</li></ul><p><strong>In this exclusive Level 3 Diploma in ICT Information Systems and Principles for IT Professionals bundle, you really hit the jackpot. 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It has been designed by our Level 3 Diploma in ICT Information Systems and Principles for IT Professionals specialists in a manner that you will be likely to find yourself head and shoulders above the others. For better learning, one to one assistance will also be provided if it's required by any learners.<br /><br />The <strong>Level 3 Diploma in ICT Information Systems and Principles for IT Professionals</strong> Bundle is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Level 3 Diploma in ICT Information Systems and Principles for IT Professionals bundle course has been created with twenty-five premium courses to provide our learners with the best learning experience possible to increase their understanding of their chosen field.<br /><br />This <strong>Level 3 Diploma in ICT Information Systems and Principles for IT Professionals</strong> Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into Level 3 Diploma in ICT Information Systems and Principles for IT Professionals Elementary modules, allowing our students to grasp each lesson quickly.</p><p>The <strong>Level 3 Diploma in ICT Information Systems and Principles for IT Professionals</strong> course is self-paced and can be taken from the comfort of your home, office, or on the go! With our Student ID card you will get discounts on things like music, food, travel and clothes etc.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        250 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>This <strong>Level 3 Diploma in ICT Information Systems and Principles for IT Professionals </strong>training is suitable for -</p><ul><li>Students</li><li>Recent graduates</li><li>Job Seekers</li><li>Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Level 3 Diploma in ICT Information Systems and Principles for IT Professionals</li><li>Further wants to study Pearson BTEC Level 2 Certificate in ICT Systems and Principles</li></ul><p><strong>Please Note:</strong> Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>To participate in this <strong>Level 3 Diploma in ICT Information Systems and Principles for IT Professionals </strong>course, all you need is -</p><ul><li>A smart device</li><li>A secure internet connection</li><li>And a keen interest in Level 3 Diploma in ICT Information Systems and Principles for IT Professionals</li></ul>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>You will be able to kickstart your <strong>Level 3 Diploma in ICT Information Systems and Principles for IT Professionals </strong>career because this course includes various courses as a bonus. This bundle is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Level 3 Diploma in ICT Information Systems and Principles for IT Professionals career opportunities</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
            <div><ul><li>CPD Accredited e-Certificate - Free</li><li>CPD Accredited Hardcopy Certificate - Free</li><li>Enrolment Letter - Free</li><li>Student ID Card - Free</li></ul></div>

                        </div>

Studyhub UK

Certificate in Further Education & Training (Cert Ed)

Cert Iv

IT Certifications

Certificate in Education & Training (CET)

Diploma in Professional Studies (DPS)

ICDL (International Certification of Digital Literacy)

Level 3 Diploma in ICT Information Systems and Principles for IT Professionals

<p>Tired of searching and accumulating all the relevant courses for this specific field? It takes a substantial amount of your time and, more importantly, costs you a fortune! Well, we have just come up with the ultimate solution for you by giving this all-inclusive Google Analytics mega bundle.</p><p>This 40 courses mega bundle keeps you up-to-date in this field and takes you one step ahead of others. Keeping in mind the latest advancements in this ever-emerging sector, the Google Analytics bundle covers all the state-of-the-art tools and techniques required to become a competent worker in this area.</p><p>You will encounter specific courses relevant to the sector. We take you from the most introductory fundamentals to advance knowledge in a step-by-step manner. In addition, the Google Analytics bundle also consists of courses related to some soft skills that you will need to succeed in any industry or job sector.</p><p><strong>This </strong><strong>Google Analytics </strong><strong>Bundle consists of the following premium courses:</strong></p><ul><li>Course 01: Google Data Studio: Data Analytics</li><li>Course 02: Diploma in Data Analysis Fundamentals</li><li>Course 03: Learn How To Optimize Your Google My Business Page In 2016</li><li>Course 04: How To Do Keyword Research For SEO &amp; Ranking On Google</li><li>Course 05: Excel Pivot Tables for Data Reporting</li><li>Course 06: Research Methods in Business</li><li>Course 07: Business Intelligence and Data Mining</li><li>Course 08: Microsoft Power BI - Master Power BI in 90 Minutes!</li><li>Course 09: PowerBI Formulas</li><li>Course 10: Digital Marketing for Beginners to Advanced</li><li>Course 11: Digital Marketing Starting an online E-Commerce Store</li><li>Course 12: Marketing Strategies for Business</li><li>Course 13: Strategic Planning and Analysis for Marketing</li><li>Course 14: Statistical Analysis</li><li>Course 15: Ultimate Social Media Marketing course</li><li>Course 16: Python Course</li><li>Course 17: Complete Online Marketing &amp; Advertising Course</li><li>Course 18: Social Media Marketing-The Step by Step Guide</li><li>Course 19: Create Your First Responsive Website</li><li>Course 20: Data Science &amp; Machine Learning with Python</li><li>Course 21: Fundamentals of Business Analysis</li><li>Course 22: Excel Data Analysis</li><li>Course 23: Quick Data Science Approach from Scratch</li><li>Course 24: Basics of WordPress: Create Unlimited Websites</li><li>Course 25: The Ultimate SEO Blueprint - Easily Ranking #1 On Google</li><li>Course 26: Complete Communication Skills Master Class for Life</li><li>Course 27: Public Speaking</li><li>Course 28: Minute Taking Executive Training</li><li>Course 29: Receptionist Skills</li><li>Course 30: Time Management Training - Online Course</li></ul><p><strong>Moreover, this bundles include 10 career-focused courses:</strong></p><ul><li>Course 01: Career Development Plan Fundamentals</li><li>Course 02: CV Writing and Job Searching</li><li>Course 03: Interview Skills: Ace the Interview</li><li>Course 04: Video Job Interview for Job Seekers</li><li>Course 05: Create a Professional LinkedIn Profile</li><li>Course 06: Business English Perfection Course</li><li>Course 07: Networking Skills for Personal Success</li><li>Course 08: Boost Your Confidence and Self-Esteem</li><li>Course 09: Public Speaking Training</li><li>Course 10: Learn to Fight Procrastination</li></ul><p>Our cutting-edge learning package offers top-notch digital aid and first-rate tutor support. You will acquire the crucial hard and soft skills needed for career advancement because this bundle has been thoroughly examined and is career-friendly. So don't overthink! Enrol today.</p><p><strong>Learning Outcomes</strong></p><p>This unique Google Analytics mega bundle will help you to-</p><ul><li>Quench your thirst for knowledge</li><li>Be up-to-date about the latest advancements</li><li>Achieve your dream career goal in this sector</li><li>Know the applicable rules and regulations needed for a professional in this area</li><li>Acquire some valuable knowledge related to Google Analytics to uplift your morale</li></ul><p>The bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your expertise and essential knowledge, which will assist you in reaching your goal. Moreover, you can learn from any place in your own time without travelling for classes.</p><p><strong>Certificate:</strong></p><ul><li><strong>PDF Certificate: Free for all </strong><strong>40</strong><strong> courses</strong></li><li><strong>Hard Copy Certificate: Free (For The Title Course: Previously it was £10)</strong></li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        400 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>The Google Analytics bundle is designed to assist anyone with a curious mind, anyone looking to boost their CVs or individuals looking to upgrade their career to the next level can also benefit from the learning materials.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>The courses in this bundle has been designed to be fully compatible with tablets and smartphones.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This Google Analytics bundle will give you an edge over other competitors and will open the doors for you to a plethora of career opportunities.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>You will get the Hard Copy certificate for the title course (<strong>Google Data Studio: Data Analytics</strong>) absolutely Free! Other Hard Copy certificates are available for £10 each. </p><p><strong>Please Note:</strong> The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.</p> </div>

                        </div>

Google Analytics for Everyone - Zero to Hero

<p>Unlock Your Potential with the Ultimate Software Developer Training Bundle!</p><p>Are you looking to boost your career in the tech industry? Do you want to expand your skillset and become a well-rounded software developer? Then look no further than our 20-in-1 Ultimate Software Developer bundle!</p><p>This comprehensive bundle includes 25 courses that cover everything from IT support and network security to ethical hacking and web development. You'll learn the latest technologies and industry-standard tools, all taught by expert instructors with real-world experience.</p><p>But that's not all - we also offer 5 career-guided courses to help you land your dream job. You'll learn how to create a professional LinkedIn profile, write a winning CV, ace your job interviews, and more.</p><p>Whether you're a beginner or an experienced professional, this bundle is perfect for anyone who wants to take their software development career to the next level. And with lifetime access to all the courses, you can learn at your own pace and revisit the material whenever you need to.</p><p>Don't miss out on this incredible opportunity to supercharge your career. Enrol in the Ultimate Software Developer Training bundle today and unlock your full potential!</p><p><strong>This 20-in 1 Ultimate Software Developer bundle consists of the following Courses:</strong></p><ul><li>Course 01: IT Support Technician</li><li>Course 02: Network Security and Risk Management</li><li>Course 03: CompTIA Network</li><li>Course 04: Information Management</li><li>Course 05: Web Application Penetration Testing Course</li><li>Course 06: CompTIA Cloud+ (CV0-002)</li><li>Course 07: Learn Ethical Hacking with Kali Linux</li><li>Course 08: Computer Operating System and Troubleshooting</li><li>Course 09: Building Your Own Computer Course</li><li>Course 10: It: Ethical Hacking, IT Security and IT Cyber Attacking</li><li>Course 11: SQL Database Administrator</li><li>Course 12: MS Word Essentials - The Complete Word Course - Level 3</li><li>Course 13: Data Protection (GDPR) Practitioner</li><li>Course 14: Coding with Scratch</li><li>Course 15: Diploma in Front-End Web Development (HTML, CSS, &amp; Bootstrap)</li><li>Course 16: Data Science and Visualisation with Machine Learning</li><li>Course 17: SQL For Data Analytics &amp; Database Development</li><li>Course 18: PLC Programming Diploma</li><li>Course 19: Cisco ASA Firewall Training Course</li><li>Course 20: Create Your First Responsive Website</li></ul><p><strong>Additionally, you will get 5 other career-guided courses in this Software Developer bundle:</strong></p><ul><li>Course 01: Career Development Plan Fundamentals</li><li>Course 02: CV Writing and Job Searching</li><li>Course 03: Interview Skills: Ace the Interview</li><li>Course 04: Video Job Interview for Job Seekers</li><li>Course 05: Create a Professional LinkedIn Profile</li></ul><p><strong><em>So, stop scrolling down and procure the skills and aptitude with Apex Learning to outshine all your peers by enrolling in this </em></strong><strong>Software Developer<em> bundle</em>.</strong></p><p><strong>Learning Outcomes of Software Developer bundle </strong></p><p>This career-oriented bundle will help you to</p><ul><li>Gain the ability to excel in the role of Software Developer</li><li>Know your responsibilities as Software Developer and convey your experience to others</li><li>Gain excellent interpersonal and communication skills</li><li>Know the pros and cons of working as Software Developer</li><li>Adhere to the regulations around this area</li><li>Gain time and risk management skills to ensure efficiency</li><li>Manipulate technological advancement to become more effective</li><li>Maintain moral standards and set an example for your peers</li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        250 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>Anyone from any background can enrol in this Software Developer bundle.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This Software Developer course has been designed to be fully compatible with tablets and smartphones.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Having this expertise will increase the value of your CV and open you up to multiple job sectors.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>You will get the Hard Copy certificate for the title course (<strong>IT Support Technician</strong>) absolutely Free! Other Hard Copy certificates are available for £10 each. </p><p><strong>Please Note:</strong> The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.</p> </div>

                        </div>

Online Course Marketing

Certified in Cybersecurity (CC)

Certificate in Information Security Management Principles (CISMP)

Cyber Security

Cyber Security Foundation

Certified Cyber Professional (CCP)

Cyber Security Programming MasterClass- CPD Certified

<p>Explore your <strong>AWS cloud</strong> knowledge with our continuously updated Level 7 Diploma in AWS Cloud Practitioner library. Delve into advanced AWS topics such as serverless computing and machine learning. Learn from industry professionals who bring their experience to cloud concepts and technologies. Engaging instruction and practical application will help you pick up new skills more quickly. Enrol to learn about cloud computing, advance to a higher-paying job, and save money without compromising value.</p><p>This premium QLS-endorsed AWS Cloud Practitioner course comes with intensive study modules, dedicated tutor assistance, customer support, flexible learning opportunities and a globally recognised certification. Thus, completing our AWS Cloud Practitioner course will give you limitless possibilities anywhere and everywhere, since the value of QLS-endorsed courses is relatively high!!</p><p>What's more, the quality of our first-class course is uncompromising for both you and us. You will be taught the richest materials from this exquisite AWS Cloud Practitioner course, enabling you to open up a vast world of opportunities to grasp and gain success. For the price point, this course is an absolute steal! It's an investment you do not want to miss out on!</p><p>So, why delay any longer? Benefit your career progression by joining us today and distinguish yourself as unquestionably the most skilled in your workplace!</p><p><strong>Why Learn with us: </strong></p><p>As one of the leading e-learning service providers globally, we strive to provide all our learners with the best e-learning experience possible that can make a real difference in their career progression.</p><p><strong>Our Service for the </strong><strong>AWS Cloud Practitioner</strong><strong> Includes:</strong></p><ul><li>Intensive Study Notes</li><li>Tutor Support</li><li>Customer Support</li><li>Assignment Help</li><li>QLS Endorsed Certificate</li><li>24/7 Learning Portal Access</li><li>Widely Compatible Study Materials</li></ul><p><strong>Course Curriculum of </strong><strong>AWS Cloud Practitioner</strong></p><ul><li>Introduction to Cloud Computing</li><li>First Steps into Amazon Web Services</li><li>Identity and Access Management (IAM)</li><li>Networking AWS-Virtual Private Clouds</li><li>Elastic Compute Cloud (EC2)</li><li>Amazon Storage</li><li>Fault Tolerance and Elasticity</li><li>DNS and Content Delivery Networks</li><li>Monitoring, Auditing and Alerts</li><li>Databases</li><li>Serverless Computing</li><li>Security and Compliance</li><li>AWS Billing and Support Services</li></ul><p><strong>Assessment &amp; Certification</strong></p><p>Learners must submit a comprehensive summarised assignment on all the units that our expert tutor will assess if all the learning outcomes are met as per the standard set by QLS. After the quality check, the learner will receive the AWS Cloud Practitioner certificate.</p><p><strong>Endorsed Certificate of Achievement from the Quality Licence Scheme.</strong></p><p>An endorsed certificate will be issued to learners at the course's end to recognise completion. Provided that the learner completes all the assessments of a system, he can claim a certificate.</p><p><strong>Endorsement:</strong></p><p>QLS endorsed this certified course as a highly qualified, non-regulated provision and training programme. There will be a trainer to answer all your questions, including your progression routes into further higher education.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        10 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>Our course is open to everyone. This <strong>Level 7 Diploma in AWS Cloud Practitioner </strong>is ideal for those who aspire to gain in-depth knowledge &amp; efficient skills to embark into the relevant sector as a promising potential.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>There are no formal requirements needed for this <strong>Level 7 Diploma in AWS Cloud Practitioner </strong>course. So, learners do not require prior qualifications to enrol in this course.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p><strong>Level 7 Diploma in AWS Cloud Practitioner</strong> opens opportunities in the following job roles:</p><ul><li>Principal Cloud Solutions Architect (£80,000 - £105,000)</li><li>AWS Cloud DevOps Engineer (£70,000 - £85,000)</li><li>Cybersecurity Analyst - London - Banking - Cloud Platforms (£50,000 - £55,000)</li><li>Software Developer Go, PHP, AWS (£40,000 - £40,001)</li><li>Salesforce Marketing Cloud Consultant (£50,000 - £75,000)</li></ul>
                        </div>

Kingston Open College

Psychological Wellbeing Practitioner

Clinical Practitioner

AWS Certified Developer

AWS Certified Cloud Practitioner

NLP Practitioner

AWS Certified Solutions Architect

QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support | All-Inclusive Cost

Level 7 Diploma in AWS Cloud Practitioner - QLS Endorsed

<div id="course-pills-1">Duration<p>1 Days</p><p>6 CPD hours</p>This course is intended for<p></p><p>The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don?t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful.</p><p></p><p></p><p>This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. </p><p></p>Prerequisites<p>Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services.   Specifically:  </p><ul> <li>Experience using computers and the internet.</li> <li>Interest in use cases for AI applications and machine learning models. </li> <li>A willingness to learn through hands-on exp...</li><p></p></ul></div><div id="course-pills-2"><h3>1 - Fundamental AI Concepts</h3> <ul> <li>Understand machine learning</li> <li>Understand computer vision</li> <li>Understand natural language processing</li> <li>Understand document intelligence and knowledge mining</li> <li>Understand generative AI</li> <li>Challenges and risks with AI</li> <li>Understand Responsible AI</li> </ul> <h3>2 - Fundamentals of machine learning</h3> <ul> <li>What is machine learning?</li> <li>Types of machine learning</li> <li>Regression</li> <li>Binary classification</li> <li>Multiclass classification</li> <li>Clustering</li> <li>Deep learning</li> <li>Azure Machine Learning</li> </ul> <h3>3 - Fundamentals of Azure AI services</h3> <ul> <li>AI services on the Azure platform</li> <li>Create Azure AI service resources</li> <li>Use Azure AI services</li> <li>Understand authentication for Azure AI services</li> </ul> <h3>4 - Fundamentals of Computer Vision</h3> <ul> <li>Images and image processing</li> <li>Machine learning for computer vision</li> <li>Azure AI Vision</li> </ul> <h3>5 - Fundamentals of Facial Recognition</h3> <ul> <li>Understand Face analysis</li> <li>Get started with Face analysis on Azure</li> </ul> <h3>6 - Fundamentals of optical character recognition</h3> <ul> <li>Get started with Vision Studio on Azure</li> </ul> <h3>7 - Fundamentals of Text Analysis with the Language Service</h3> <ul> <li>Understand Text Analytics</li> <li>Get started with text analysis</li> </ul> <h3>8 - Fundamentals of question answering with the Language Service</h3> <ul> <li>Understand question answering</li> <li>Get started with the Language service and Azure Bot Service</li> </ul> <h3>9 - Fundamentals of conversational language understanding</h3> <ul> <li>Describe conversational language understanding</li> <li>Get started with conversational language understanding in Azure</li> </ul> <h3>10 - Fundamentals of Azure AI Speech</h3> <ul> <li>Understand speech recognition and synthesis</li> <li>Get started with speech on Azure</li> </ul> <h3>11 - Fundamentals of Azure AI Document Intelligence</h3> <ul> <li>Explore capabilities of document intelligence</li> <li>Get started with receipt analysis on Azure</li> </ul> <h3>12 - Fundamentals of Knowledge Mining with Azure Cognitive Search</h3> <ul> <li>What is Azure Cognitive Search?</li> <li>Identify elements of a search solution</li> <li>Use a skillset to define an enrichment pipeline</li> <li>Understand indexes</li> <li>Use an indexer to build an index</li> <li>Persist enriched data in a knowledge store</li> <li>Create an index in the Azure portal</li> <li>Query data in an Azure Cognitive Search index</li> </ul> <h3>13 - Fundamentals of Generative AI</h3> <ul> <li>What is generative AI?</li> <li>Large language models</li> <li>What is Azure OpenAI?</li> <li>What are copilots?</li> <li>Improve generative AI responses with prompt engineering</li> </ul> <h3>14 - Fundamentals of Azure OpenAI Service</h3> <ul> <li>What is generative AI</li> <li>Describe Azure OpenAI</li> <li>How to use Azure OpenAI</li> <li>Understand OpenAI's natural language capabilities</li> <li>Understand OpenAI code generation capabilities</li> <li>Understand OpenAI's image generation capabilities</li> <li>Describe Azure OpenAI's access and responsible AI policies</li> </ul> <h3>15 - Fundamentals of Responsible Generative AI</h3> <ul> <li>Plan a responsible generative AI solution</li> <li>Identify potential harms</li> <li>Measure potential harms</li> <li>Mitigate potential harms</li> <li>Operate a responsible generative AI solution</li> </ul></div><div id="course-pills-3"><h4>Additional course details:</h4><br /><p>Nexus Humans AI-900T00 - Microsoft Azure AI Fundamentals training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. </p><p></p> This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. <p></p>Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.  <p></p>While we feel this is the best course for the AI-900T00 - Microsoft Azure AI Fundamentals course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.  <p></p>Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.<p></p></div>

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

Azure Machine Learning

Microsoft AI-900

AI-900T00 Microsoft Azure AI Fundamentals

<p>If you aim to enhance your Machine Learning &amp; Artificial Intelligence skills, our comprehensive Machine Learning &amp; Artificial Intelligence course is perfect for you. Designed for success, this Machine Learning &amp; Artificial Intelligence course covers everything from basics to advanced topics in Machine Learning &amp; Artificial Intelligence.</p><p>Each lesson in this Machine Learning &amp; Artificial Intelligence course is crafted for easy understanding, enabling you to become proficient in Machine Learning &amp; Artificial Intelligence. Whether you are a beginner or looking to sharpen your existing skills, this Machine Learning &amp; Artificial Intelligence is the ideal choice.</p><p>With our Machine Learning &amp; Artificial Intelligence exclusive bundle, you will get<strong> a PDF Certificate, PDF Transcript and Digital Student ID Card (worth £50) Absolutely FREE. </strong></p><p><strong>Courses are Included in This Bundle:</strong></p><ul><li><strong>Course 01: </strong>Machine Learning Basics</li><li><strong>Course 02: </strong>Hands-on Machine Learning Project - Auto Image Captioning for Social Media</li><li><strong>Course 03: </strong>Machine Learning with Python Course</li><li><strong>Course 04: </strong>Project on Deep Learning - Artificial Neural Network</li><li><strong>Course 05: </strong>Data Science &amp; Machine Learning with R Training</li><li><strong>Course 06: </strong>ChatGPT for Marketing and Productivity with AI Tools</li></ul><p><strong>Why Choose Our Course?</strong></p><ul><li>FREE Machine Learning &amp; Artificial Intelligence certificate accredited</li><li>Get a free student ID card with Machine Learning &amp; Artificial Intelligence Training</li><li>Get instant access to this Machine Learning &amp; Artificial Intelligence course.</li><li>Learn Machine Learning &amp; Artificial Intelligence from anywhere in the world</li><li>Machine Learning &amp; Artificial Intelligence is affordable and simple to understand</li><li>This bundle is an entirely online, interactive lesson with voiceover audio</li><li>Lifetime access to the Machine Learning &amp; Artificial Intelligence course materials</li><li>The Machine Learning &amp; Artificial Intelligence comes with 24/7 tutor support</li></ul><p>So enrol now in this Machine Learning &amp; Artificial Intelligence Today to advance your career!</p> <p>Start your learning journey straightaway!</p><p>This Machine Learning &amp; Artificial Intelligence's curriculum has been designed by Machine Learning &amp; Artificial Intelligence experts with years of Machine Learning &amp; Artificial Intelligence experience behind them. The Machine Learning &amp; Artificial Intelligence course is extremely dynamic and well-paced to help you understand Machine Learning &amp; Artificial Intelligence with ease. You'll discover how to master Machine Learning &amp; Artificial Intelligence skills while exploring relevant and essential topics.</p><p><strong>Assessment Process</strong></p><p>Once you have completed all the courses in the Machine Learning &amp; Artificial Intelligence bundle, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        60 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>This Machine Learning &amp; Artificial Intelligence bundle is suitable for everyone.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This Machine Learning &amp; Artificial Intelligence bundle will allow you to kickstart or take your career in the related sector to the next stage.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Digital certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited  Hard copy certificate</h4>
        <p>
            Hard copy certificate -
            £29
        </p>
            <div><p>If you are an international student, you will be required to pay an additional fee of <strong>10 GBP</strong> for international delivery, and <strong>4.99 GBP</strong> for delivery within the UK, for each certificate</p></div>

                        </div>

If you aim to enhance your Machine Learning & Artificial Intelligence skills, our comprehensive Machine Learning & Artificial Intelligence course is perfect for you. Designed for success, this Machine Learning & Artificial Intelligence course covers everything from basics to advanced topics in Machine Learning & Artificial Intelligence.
Each lesson in this Machine Learning & Artificial Intelligence course is crafted for easy understanding, enabling you to become proficient in Machine Learning & Artificial Intelligence. Whether you are a beginner or looking to sharpen your existing skills, this Machine Learning & Artificial Intelligence is the ideal choice.
With our Machine Learning & Artificial Intelligence exclusive bundle, you will get a PDF Certificate, PDF Transcript and Digital Student ID Card (worth £50) Absolutely FREE. 
Courses are Included in This Machine Learning & Artificial Intelligence Bundle:
Course 01: Machine Learning Basics
Course 02: Hands-on Machine Learning Project - Auto Image Captioning for Social Media
Course 03: Machine Learning with Python Course
Course 04: Project on Deep Learning - Artificial Neural Network
Course 05: Data Science & Machine Learning with R Training
Course 06: ChatGPT for Marketing and Productivity with AI Tools
Learning Outcomes of this Machine Learning & Artificial Intelligence
Understand the foundational concepts of machine learning and its applications.
Gain practical experience through hands-on machine learning projects and tools.
Master Python programming for effective machine learning applications and tasks.
Develop deep learning models using artificial neural networks effectively.
Apply data science techniques using R for comprehensive data analysis.
Learn to utilise AI tools for marketing and enhancing productivity in business.
Why Choose Our Course?
FREE Machine Learning & Artificial Intelligence certificate accredited
Get a free student ID card with Machine Learning & Artificial Intelligence Training
Get instant access to this Machine Learning & Artificial Intelligence course.
Learn Machine Learning & Artificial Intelligence from anywhere in the world
Machine Learning & Artificial Intelligence is affordable and simple to understand
This bundle is an entirely online, interactive lesson with voiceover audio
Lifetime access to the Machine Learning & Artificial Intelligence course materials
The Machine Learning & Artificial Intelligence comes with 24/7 tutor support
So enrol now in this Machine Learning & Artificial Intelligence Today to advance your career!



Start your learning journey straightaway with Machine Learning & Artificial Intelligence!
This Machine Learning & Artificial Intelligence's curriculum has been designed by Machine Learning & Artificial Intelligence experts with years of Machine Learning & Artificial Intelligence experience behind them. The Machine Learning & Artificial Intelligence course is extremely dynamic and well-paced to help you understand Machine Learning & Artificial Intelligence with ease. You'll discover how to master Machine Learning & Artificial Intelligence skills while exploring relevant and essential topics.
*** Course Curriculum ***
Course 01: Machine Learning Basics
Section 01: Introduction
Section 02: Regression
Section 03: Predictors
Section 04: Minitab
Section 05: Regression Trees
Section 06: Binary Logistics Regression
Section 07: Classification Trees
Section 08: Data Cleaning
Section 09: Data Models
Section 10: Learning Success
Course 02: Hands-on Machine Learning Project - Auto Image Captioning for Social Media
Section 01: Introduction
Section 02: Building the Auto Image Captioning
Section 03: Deployment of Machine Learning App
Assessment Process of Machine Learning & Artificial Intelligence
Once you have completed all the courses in the Machine Learning & Artificial Intelligence bundle, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards.
 CPD 
60 CPD hours / points  Accredited by CPD Quality Standards



 Who is this course for? 
This Machine Learning & Artificial Intelligence bundle is suitable for everyone.




 Requirements 
You will not need any prior background or expertise in this Machine Learning & Artificial Intelligence.




 Career path 
This Machine Learning & Artificial Intelligence bundle will allow you to kickstart or take your career in the related sector to the next stage.



 Certificates 
CPD Accredited Digital certificate
 Digital certificate - Included 
CPD Accredited Hard copy certificate
 Hard copy certificate - £29 
If you are an international student, you will be required to pay an additional fee of 10 GBP for international delivery, and 4.99 GBP for delivery within the UK, for each certificate

Learning & Development

Managed Learning Programme (MLP)

Machine Learning (ML)

Trainers Course

Machine Learning & Artificial Intelligence

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p></p><p>Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure.</p><p></p><p></p><p>AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language.</p><p></p>Prerequisites<p>Before attending this course, students must have:  </p><li>Knowledge of Microsoft Azure and ability to navigate the Azure portal  </li><li>Knowledge of either C# or Python  </li><li>Familiarity with JSON and REST programming semantics  <br />  Recommended course prerequisites  </li><li>AI-900T00: Microsoft Azure AI Fundamentals course<p></p></li></div><div id="course-pills-2"><h3>1 - Prepare to develop AI solutions on Azure</h3> <ul> <li>Define artificial intelligence</li> <li>Understand AI-related terms</li> <li>Understand considerations for AI Engineers</li> <li>Understand considerations for responsible AI</li> <li>Understand capabilities of Azure Machine Learning</li> <li>Understand capabilities of Azure AI Services</li> <li>Understand capabilities of the Azure Bot Service</li> <li>Understand capabilities of Azure Cognitive Search</li> </ul> <h3>2 - Create and consume Azure AI services</h3> <ul> <li>Provision an Azure AI services resource</li> <li>Identify endpoints and keys</li> <li>Use a REST API</li> <li>Use an SDK</li> </ul> <h3>3 - Secure Azure AI services</h3> <ul> <li>Consider authentication</li> <li>Implement network security</li> </ul> <h3>4 - Monitor Azure AI services</h3> <ul> <li>Monitor cost</li> <li>Create alerts</li> <li>View metrics</li> <li>Manage diagnostic logging</li> </ul> <h3>5 - Deploy Azure AI services in containers</h3> <ul> <li>Understand containers</li> <li>Use Azure AI services containers</li> </ul> <h3>6 - Analyze images</h3> <ul> <li>Provision an Azure AI Vision resource</li> <li>Analyze an image</li> <li>Generate a smart-cropped thumbnail</li> </ul> <h3>7 - Classify images</h3> <ul> <li>Provision Azure resources for Azure AI Custom Vision</li> <li>Understand image classification</li> <li>Train an image classifier</li> </ul> <h3>8 - Detect, analyze, and recognize faces</h3> <ul> <li>Identify options for face detection analysis and identification</li> <li>Understand considerations for face analysis</li> <li>Detect faces with the Azure AI Vision service</li> <li>Understand capabilities of the face service</li> <li>Compare and match detected faces</li> <li>Implement facial recognition</li> </ul> <h3>9 - Read Text in images and documents with the Azure AI Vision Service</h3> <ul> <li>Explore Azure AI Vision options for reading text</li> <li>Use the Read API</li> </ul> <h3>10 - Analyze video</h3> <ul> <li>Understand Azure Video Indexer capabilities</li> <li>Extract custom insights</li> <li>Use Video Analyzer widgets and APIs</li> </ul> <h3>11 - Analyze text with Azure AI Language</h3> <ul> <li>Provision an Azure AI Language resource</li> <li>Detect language</li> <li>Extract key phrases</li> <li>Analyze sentiment</li> <li>Extract entities</li> <li>Extract linked entities</li> </ul> <h3>12 - Build a question answering solution</h3> <ul> <li>Understand question answering</li> <li>Compare question answering to Azure AI Language understanding</li> <li>Create a knowledge base</li> <li>Implement multi-turn conversation</li> <li>Test and publish a knowledge base</li> <li>Use a knowledge base</li> <li>Improve question answering performance</li> </ul> <h3>13 - Build a conversational language understanding model</h3> <ul> <li>Understand prebuilt capabilities of the Azure AI Language service</li> <li>Understand resources for building a conversational language understanding model</li> <li>Define intents, utterances, and entities</li> <li>Use patterns to differentiate similar utterances</li> <li>Use pre-built entity components</li> <li>Train, test, publish, and review a conversational language understanding model</li> </ul> <h3>14 - Create a custom text classification solution</h3> <ul> <li>Understand types of classification projects</li> <li>Understand how to build text classification projects</li> </ul> <h3>15 - Create a custom named entity extraction solution</h3> <ul> <li>Understand custom named entity recognition</li> <li>Label your data</li> <li>Train and evaluate your model</li> </ul> <h3>16 - Translate text with Azure AI Translator service</h3> <ul> <li>Provision an Azure AI Translator resource</li> <li>Specify translation options</li> <li>Define custom translations</li> </ul> <h3>17 - Create speech-enabled apps with Azure AI services</h3> <ul> <li>Provision an Azure resource for speech</li> <li>Use the Azure AI Speech to Text API</li> <li>Use the text to speech API</li> <li>Configure audio format and voices</li> <li>Use Speech Synthesis Markup Language</li> </ul> <h3>18 - Translate speech with the Azure AI Speech service</h3> <ul> <li>Provision an Azure resource for speech translation</li> <li>Translate speech to text</li> <li>Synthesize translations</li> </ul> <h3>19 - Create an Azure AI Search solution</h3> <ul> <li>Manage capacity</li> <li>Understand search components</li> <li>Understand the indexing process</li> <li>Search an index</li> <li>Apply filtering and sorting</li> <li>Enhance the index</li> </ul> <h3>20 - Create a custom skill for Azure AI Search</h3> <ul> <li>Create a custom skill</li> <li>Add a custom skill to a skillset</li> </ul> <h3>21 - Create a knowledge store with Azure AI Search</h3> <ul> <li>Define projections</li> <li>Define a knowledge store</li> </ul> <h3>22 - Plan an Azure AI Document Intelligence solution</h3> <ul> <li>Understand AI Document Intelligence</li> <li>Plan Azure AI Document Intelligence resources</li> <li>Choose a model type</li> </ul> <h3>23 - Use prebuilt Azure AI Document Intelligence models</h3> <ul> <li>Understand prebuilt models</li> <li>Use the General Document, Read, and Layout models</li> <li>Use financial, ID, and tax models</li> </ul> <h3>24 - Extract data from forms with Azure Document Intelligence</h3> <ul> <li>What is Azure Document Intelligence?</li> <li>Get started with Azure Document Intelligence</li> <li>Train custom models</li> <li>Use Azure Document Intelligence models</li> <li>Use the Azure Document Intelligence Studio</li> </ul> <h3>25 - Get started with Azure OpenAI Service</h3> <ul> <li>Access Azure OpenAI Service</li> <li>Use Azure OpenAI Studio</li> <li>Explore types of generative AI models</li> <li>Deploy generative AI models</li> <li>Use prompts to get completions from models</li> <li>Test models in Azure OpenAI Studio's playgrounds</li> </ul> <h3>26 - Build natural language solutions with Azure OpenAI Service</h3> <ul> <li>Integrate Azure OpenAI into your app</li> <li>Use Azure OpenAI REST API</li> <li>Use Azure OpenAI SDK</li> </ul> <h3>27 - Apply prompt engineering with Azure OpenAI Service</h3> <ul> <li>Understand prompt engineering</li> <li>Write more effective prompts</li> <li>Provide context to improve accuracy</li> </ul> <h3>28 - Generate code with Azure OpenAI Service</h3> <ul> <li>Construct code from natural language</li> <li>Complete code and assist the development process</li> <li>Fix bugs and improve your code</li> </ul> <h3>29 - Generate images with Azure OpenAI Service</h3> <ul> <li>What is DALL-E?</li> <li>Explore DALL-E in Azure OpenAI Studio</li> <li>Use the Azure OpenAI REST API to consume DALL-E models</li> </ul> <h3>30 - Use your own data with Azure OpenAI Service</h3> <ul> <li>Understand how to use your own data</li> <li>Add your own data source</li> <li>Chat with your model using your own data</li> </ul> <h3>31 - Fundamentals of Responsible Generative AI</h3> <ul> <li>Plan a responsible generative AI solution</li> <li>Identify potential harms</li> <li>Measure potential harms</li> <li>Mitigate potential harms</li> <li>Operate a responsible generative AI solution</li> </ul></div>

Microsoft AZ-104

Azure Cognitive Services

AI-102T00 Designing and Implementing an Azure AI Solution

Packt

Python

Welcome to the Bootcamp course. You will obtain a firm understanding of machine learning with this course. By doing so, you will be able to develop machine learning solutions for various challenges you might encounter and be prepared to start using machine learning at work or in technical interviews.

Python Machine Learning Bootcamp

Go from Beginner to Super Advance Level in Machine Learning Algorithms using Python and Mathematical Insights

Machine Learning with Real World Projects

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			<h2><b>Course Overview</b></h2>		</div>
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					<div><p><span>Machine learning as a programming technique has shaped the future of technology. In this course, you will learn how to build intelligent handwriting recognition apps from scratch using Python and Core ML.</span></p><p><span>The </span><b>Machine Learning for Apps Level 4 </b><span>course will teach you how to take advantage of machine learning to code like a pro and build incredible apps that can make predictions. Designed by industry experts, it covers best practices for managing projects, core concepts for creating your own ML model, building a convolutional neural network, and much more.</span></p><p><span>On successful completion, you will be able to build an amazing handwriting recognition app and convolutional neural network from scratch, and have an in-depth understanding of the core ML basics. This course is ideal for those with a basic understanding of iOS development.</span></p></div>
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					<div><p>This best selling <strong>Machine Learning for Apps Level 4 </strong>has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth <strong>Machine Learning for Apps Level 4 </strong>is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The <strong>Machine Learning for Apps Level 4 </strong>is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The <strong>Machine Learning for Apps Level 4 </strong>is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.</p><p>After successfully completing the<strong> Machine Learning for Apps Level 4</strong>, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the <strong>Machine Learning for Apps Level 4 </strong>will help you stand out from the crowd. You can also validate your certification on our website.</p><p>We know that you are busy and that time is precious, so we have designed the <strong>Machine Learning for Apps Level 4 </strong>to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. </p><p>Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.</p></div>
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Course Cloud

Machine Learning for Apps Level 4

<strong>The goal of this course is to use Python machine learning to create algorithms that you can use in the real world. You'll start with the basics of machine learning. You'll learn how to create, train, and optimize models and use these models in real-world applications.</strong>
        <p>Machine learning is a field of computer science through which you can create complex models that perform multiple functions using mathematical input. Python is a popular choice to create machine learning models due to a plethora of libraries easily accessible. This course takes you through this impressive combination of Python and machine learning, teaching you the basics of machine learning to create your own projects.

You'll begin learning about different types of machine learning models and how to choose the relevant ones for your project. You'll learn to optimize this model and apply performance metrics to track its performance. You'll also learn topics like regression, classification, and clustering to improve the performance of your model. You'll learn the basics of neural networks and use scikit-learn to perform calculations in your project.

By the end of this course, you'll have created a face recognition application using everything you've learned in this course.

The code bundle for this course is available at https://github.com/PacktPublishing/Python-Machine-Learning-Crash-Course-for-Beginners</p>
        <h2>What You Will Learn</h2><p>Train different types of machine learning models for your project<br>Prepare and clean data for your project<br>Optimize your machine learning model to best suit your project needs<br>Build your own machine learning model from scratch<br>Apply performance metrics to track the performance of your model<br>Use scikit-learn to perform calculations in your project</p>
        <h2>Audience</h2><p>This course is for Python developers who are new in the field of machine learning. No prior knowledge or experience of machine learning is required. A basic understanding of Python programming will be needed here.</p>
        <h2>Approach</h2><p>This is a hands-on course that takes you through all the machine learning concepts step-by-step while showing you real-world applications for each step.</p>
        <h2>Key Features</h2><p>Build a face recognition application from scratch * Prepare and train your data for your projects * Learn real-world applications of your algorithms</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Python-Machine-Learning-Crash-Course-for-Beginners</p>
        <h2>About the Author</h2><h3>AI Sciences</h3><p>AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.

AI sciences produce a series of courses dedicated to beginners and newcomers on techniques and methods of machine learning, statistics, artificial intelligence, and data science. They aim to help those who wish to understand techniques more easily and start with less theory and less extended reading. Today, they publish more comprehensive courses on specific topics for wider audiences.

Their courses have successfully helped more than 100,000 students master AI and data science.</p>
        <h2>Course Outline</h2><h4>1. Introduction to the Course</h4><p></p><br><h4>2. Why Machine Learning</h4><p></p><br><h4>3. Process of Learning from Data</h4><p></p><br><h4>4. Machine Learning Methods</h4><p></p><br><h4>5. Data Preparation and Preprocessing</h4><p></p><br><h4>6. Machine Learning Models and Optimization</h4><p></p><br><h4>7. Building Machine Learning Model from Scratch</h4><p></p><br><h4>8. Overfitting, Underfitting and Generalization</h4><p></p><br><h4>9. Machine Learning Model Performance Metrics</h4><p></p><br><h4>10. Dimensionality Reduction</h4><p></p><br><h4>11. Deep Learning Overview</h4><p></p><br><h4>12. Hands-on Machine Learning Project Using Scikit-Learn</h4><p></p><br><h4>13. OPTIONAL Section- Mathematics Wrap-up</h4><p></p>

The goal of this course is to use Python machine learning to create algorithms that you can use in the real world. You'll start with the basics of machine learning. You'll learn how to create, train, and optimize models and use these models in real-world applications.

Python Machine Learning Crash Course for Beginners

<strong>Begin your machine learning journey by learning all about linear regression, logistic regression, and cluster analysis</strong>
        <p>Machine Learning is one of the fundamental skills you need to become a data scientist. It's the steppingstone that will help you understand deep learning and modern data analysis techniques. 

In this course, you'll explore the three fundamental machine learning topics - linear regression, logistic regression, and cluster analysis. Even neural networks geeks (like us) can't help but admit that it's these three simple methods that data science revolves around. So, in this course, we will make the otherwise complex subject matter easy to understand and apply in practice. This course supports statistics theory with practical application of these quantitative methods in Python to help you develop skills in the context of data science. 

We've developed this course with not one but two machine learning libraries: StatsModels and sklearn. You'll be eager to complete this course and get ready to become a successful data scientist! 

All the code and supporting files for this course are available at https://github.com/PacktPublishing/Machine-Learning-101-with-Scikit-learn-and-StatsModels</p>
        <h2>What You Will Learn</h2><p>Confidently work with two of the leading ML packages: statsmodels and sklearn <br>Understand how to perform a linear regression <br>Become familiar with the ins and outs of logistic regression <br>Get to grips with carrying out cluster analysis (both flat and hierarchical) <br>Apply your skills to real-life business cases <br>Get insights into the underlying ideas behind ML models</p>
        <h2>Audience</h2><p>If you want to get acquainted with fundamental machine learning methods, become a successful data scientist, or just get started with building valuable skills in machine learning and data science, this course is for you.</p>
        <h2>Approach</h2><p>The course has a perfect blend of theory and practical knowledge to help you gain a solid understand of the concepts covered.</p>
        <h2>Key Features</h2><p>Learn machine learning with StatsModels and sklearn  * Apply machine learning skills to solve real-world business cases  * Get started with linear regression, logistic regression, and cluster analysis</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/machine-learning-101-with-scikit-learn-and-statsmodels</p>
        <h2>About the Author</h2><h3>365 Careers Ltd.</h3><p>365 Careers' courses have been taken by more than 203,000 students in 204 countries. People working at world-class firms such as Apple, PayPal, and Citibank have completed 365 Careers trainings. By choosing 365 Careers, you make sure you will learn from proven experts who have a passion for teaching, and can take you from beginner to pro in the shortest possible amount of time.

If you want to become a financial analyst, a finance manager, an FP&A analyst, an investment banker, a business executive, an entrepreneur, a business intelligence analyst, a data analyst, or a data scientist, 365 Careers' courses are the perfect place to start.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><br><h4>2. Setting Up the Working Environment</h4><p></p><br><h4>3. Linear Regression with StatsModels</h4><p></p><br><h4>4. Linear Regression with Sklearn</h4><p></p><br><h4>5. Linear Regression - Practical Example</h4><p></p><br><h4>6. Logistic Regression</h4><p></p><br><h4>7. Cluster Analysis</h4><p></p><br><h4>8. Cluster Analysis: Additional Topics</h4><p></p>

Begin your machine learning journey by learning all about linear regression, logistic regression, and cluster analysis

Machine Learning 101 with Scikit-learn and StatsModels

<strong>In this course, you will learn Python fundamentals, and the concepts of the amazing pandas data science library needed to pre-process and prepare the data for machine learning algorithms.</strong>
        <p>Machine learning is one of the most exciting fields in the hi-tech industry, gaining momentum in various applications. Companies are looking for data scientists, data engineers, and machine language (ML) experts to develop products, features, and projects that will help them unleash the power of machine learning. This course will show you how to prepare data for machine learning algorithms using Python and pandas library.

The course starts by explaining the installation process of Anaconda and Jupyter. Once you are ready with the setup, you will understand Python fundamentals, such as variables, data types, conditional statements, loops, and modules. Next, you will go through the pandas library and learn how to use it for loading real-world large datasets. Towards the end, you will learn the steps and techniques to clean data and make it ready to move into machine learning algorithms.

By the end of this course, you will be well-versed with Python fundamentals and pandas library and will be ready to take on data science projects.

The code bundle for this course is available at https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginners-Level-2</p>
        <h2>What You Will Learn</h2><p>Understand how to use Jupyter Lab for Jupyter notebooks<br>Learn Python fundamentals<br>Load large datasets from files using pandas<br>Uncover techniques to perform data analysis and exploration<br>Group, sort, export, select, filter, and clean data<br>Find out how to preview the data frame</p>
        <h2>Audience</h2><p>This course is designed for beginners looking to understand the theoretical side of machine learning and to enter the practical side of data science. You will understand the fundamentals of Python and learn how to pre-process data before using it in machine learning algorithms. There are no prerequisites for taking up this course; however, it is recommended to finish with the Machine Learning for Absolute Beginners - Level 1 course.</p>
        <h2>Approach</h2><p>With the help of exercises and activities, this course will show you how to use Python and pandas library for cleaning data before moving it into machine learning algorithms.</p>
        <h2>Key Features</h2><p>Learn how to use Python for data science and machine learning projects * Understand the interface of Jupyter lab tool * Discover how to get data ready for machine learning algorithms</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginners-Level-2 </p>
        <h2>About the Author</h2><h3>Idan Gabrieli</h3><p>Idan Gabrieli has worked in various engineering positions in Israel's high-tech industry. Idan has gained extensive experience with hundreds of business companies, transforming their challenges and opportunities into practical use cases and leveraging cutting-edge technologies.

Idan's expertise spans multiple domains, including cloud computing, machine learning, data science, and electronics. Since 2014, Idan has created and published online courses on various topics worldwide. Idan is recognized as a high-rated instructor by leading educational providers.

Idan simplifies complex technology and provides high-quality educational content with specific learning objectives that are well-structured, combining various multimedia teaching options.</p>
        <h2>Course Outline</h2><h4>1. Getting Started with Level 2!</h4><p></p><br><h4>2. Python Fundamentals for Data Science</h4><p></p><br><h4>3. Introduction to the Pandas Library</h4><p></p><br><h4>4. Loading Data into a DataFrame</h4><p></p><br><h4>5. Data Cleaning and Transformation</h4><p></p><br><h4>6. Course Summary</h4><p></p>

In this course, you will learn Python fundamentals, and the concepts of the amazing pandas data science library needed to pre-process and prepare the data for machine learning algorithms.

Machine Learning for Absolute Beginners - Level 2

<strong>Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning &amp; More!</strong>
        <p>Do you ever want to be a data scientist and build Machine Learning projects that can solve real-life problems? If yes, then this course is perfect for you.
You will train machine learning algorithms to classify flowers, predict house price, identify handwritings or digits, identify staff that is most likely to leave prematurely, detect cancer cells and much more!
Inside the course, you'll learn how to:
&bull;	Set up a Python development environment correctly
&bull;	Gain complete machine learning toolsets to tackle most real-world problems
&bull;	Understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accuracy, confusion matrix, prevision, recall, etc. and when to use them.
&bull;	Combine multiple models with by bagging, boosting or stacking
&bull;	Make use to unsupervised Machine Learning (ML) algorithms such as Hierarchical clustering, k-means clustering etc. to understand your data
&bull;	Develop in Jupyter (IPython) notebook, Spyder and various IDE
&bull;	Communicate visually and effectively with Matplotlib and Seaborn
&bull;	Engineer new features to improve algorithm predictions
&bull;	Make use of train/test, K-fold and Stratified K-fold cross-validation to select the correct model and predict model perform with unseen data
&bull;	Use SVM for handwriting recognition, and classification problems in general
&bull;	Use decision trees to predict staff attrition
&bull;	Apply the association rule to retail shopping datasets
&bull;	And much more!
By the end of this course, you will have a Portfolio of 12 Machine Learning projects that will help you land your dream job or enable you to solve real-life problems in your business, job or personal life with Machine Learning algorithms.</p>
        <h2>What You Will Learn</h2><p>&bull;&nbsp;&nbsp;Learn to Build Powerful Machine Learning Models to Solve Any Problem<br>&bull;&nbsp;&nbsp;Learn to Train machine learning algorithms to predict house prices, identify handwriting, detect cancer cells &amp; more</p>
        <h2>Audience</h2><p>A newbie who wants to learn machine learning algorithm with Python. Anyone who has a deep interest in the practical application of machine learning to real world problems. Anyone wishes to move beyond the basics and develop an understanding of the whole range of machine learning algorithms. Any intermediate to advanced EXCEL users who is unable to work with large datasets. Anyone interested to present their findings in a professional and convincing manner. Anyone who wishes to start or transit into a career as a data scientist. Anyone who wants to apply machine learning to their domain.</p>
        <h2>Approach</h2><p>You'll go from beginner to extremely high-level and your instructor will build each algorithm with you step by step on screen.</p>
        <h2>Key Features</h2><p>&bull;&nbsp;&nbsp;Solve any problem in your business or job with powerful Machine Learning models * &bull;&nbsp;&nbsp;Go from zero to hero in Python, Seaborn, Matplotlib, Scikit-Learn, SVM, and unsupervised Machine Learning etc.</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/the-complete-machine-learning-course-with-python</p>
        <h2>About the Author</h2><h3>Anthony Ng</h3><p>Anthony Ng has spent almost 10 years in the education sector covering topics such as algorithmic trading, financial data analytics, investment, and portfolio management and more. He has worked in various financial institutions and has assisted Quantopian to conduct Algorithmic Trading Workshops in Singapore since 2016. He has also presented in QuantCon Singapore 2016 and 2017. He is passionate about finance, data science and Python and enjoys researching, teaching and sharing knowledge. He holds a Master of Science in Financial Engineering from NUS Singapore and MBA and Bcom from Otago University.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What Does the Course Cover?</p><p style='margin: 0'>Introduction: What Does the Course Cover?</p></td></tr></tbody></table><br><h4>2. Getting Started with Anaconda</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. [Windows OS] Downloading & Installing Anaconda</p><p style='margin: 0'>Getting Started with Anaconda: [Windows OS] Downloading &amp; Installing Anaconda</p></td></tr><tr><td style='padding: 15px;'><p>2. [Windows OS] Managing Environment</p><p style='margin: 0'>Getting Started with Anaconda: [Windows OS] Managing Environment</p></td></tr><tr><td style='padding: 15px;'><p>3. Navigating the Spyder & Jupyter Notebook Interface</p><p style='margin: 0'>Getting Started with Anaconda: Navigating the Spyder &amp; Jupyter Notebook Interface</p></td></tr><tr><td style='padding: 15px;'><p>4. Downloading the IRIS Datasets</p><p style='margin: 0'>Getting Started with Anaconda: Downloading the IRIS Datasets</p></td></tr><tr><td style='padding: 15px;'><p>5. Data Exploration and Analysis</p><p style='margin: 0'>Getting Started with Anaconda: Data Exploration and Analysis</p></td></tr><tr><td style='padding: 15px;'><p>6. Presenting Your Data</p><p style='margin: 0'>Getting Started with Anaconda: Presenting Your Data</p></td></tr></tbody></table><br><h4>3. Regression</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Regression: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Categories of Machine Learning</p><p style='margin: 0'>Regression: Categories of Machine Learning</p></td></tr><tr><td style='padding: 15px;'><p>3. Working with Scikit-Learn</p><p style='margin: 0'>Regression: Working with Scikit-Learn</p></td></tr><tr><td style='padding: 15px;'><p>4. Boston Housing Data - EDA</p><p style='margin: 0'>Regression: Boston Housing Data - EDA</p></td></tr><tr><td style='padding: 15px;'><p>5. Correlation Analysis and Feature Selection</p><p style='margin: 0'>Regression: Correlation Analysis and Feature Selection</p></td></tr><tr><td style='padding: 15px;'><p>6. Simple Linear Regression Modelling with Boston Housing Data</p><p style='margin: 0'>Regression: Simple Linear Regression Modelling with Boston Housing Data</p></td></tr><tr><td style='padding: 15px;'><p>7. Robust Regression</p><p style='margin: 0'>Regression: Robust Regression</p></td></tr><tr><td style='padding: 15px;'><p>8. Evaluate Model Performance</p><p style='margin: 0'>Regression: Evaluate Model Performance</p></td></tr><tr><td style='padding: 15px;'><p>9. Multiple Regression with statsmodel</p><p style='margin: 0'>Regression: Multiple Regression with statsmodel</p></td></tr><tr><td style='padding: 15px;'><p>10. Multiple Regression and Feature Importance</p><p style='margin: 0'>Regression: Multiple Regression and Feature Importance</p></td></tr><tr><td style='padding: 15px;'><p>11. Ordinary Least Square Regression and Gradient Descent</p><p style='margin: 0'>Regression: Ordinary Least Square Regression and Gradient Descent</p></td></tr><tr><td style='padding: 15px;'><p>12. Regularised Method for Regression</p><p style='margin: 0'>Regression: Regularised Method for Regression</p></td></tr><tr><td style='padding: 15px;'><p>13. Polynomial Regression</p><p style='margin: 0'>Regression: Polynomial Regression</p></td></tr><tr><td style='padding: 15px;'><p>14. Dealing with Non-linear relationships</p><p style='margin: 0'>Regression: Dealing with Non-linear relationships</p></td></tr><tr><td style='padding: 15px;'><p>15. Feature Importance Revisited</p><p style='margin: 0'>Regression: Feature Importance Revisited</p></td></tr><tr><td style='padding: 15px;'><p>16. Data Pre-Processing 1</p><p style='margin: 0'>Regression: Data Pre-Processing 1</p></td></tr><tr><td style='padding: 15px;'><p>17. Data Pre-Processing 2</p><p style='margin: 0'>Regression: Data Pre-Processing 2</p></td></tr><tr><td style='padding: 15px;'><p>18. Variance Bias Trade Off - Validation Curve</p><p style='margin: 0'>Regression: Variance Bias Trade Off - Validation Curve</p></td></tr><tr><td style='padding: 15px;'><p>19. Variance Bias Trade Off - Learning Curve</p><p style='margin: 0'>Regression: Variance Bias Trade Off - Learning Curve</p></td></tr><tr><td style='padding: 15px;'><p>20. Cross Validation</p><p style='margin: 0'>Regression: Cross Validation</p></td></tr></tbody></table><br><h4>4. Classification</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Classification: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Logistic Regression 1</p><p style='margin: 0'>Classification: Logistic Regression 1</p></td></tr><tr><td style='padding: 15px;'><p>3. Logistic Regression 2</p><p style='margin: 0'>Classification: Logistic Regression 2</p></td></tr><tr><td style='padding: 15px;'><p>4. MNIST Project 1 - Introduction</p><p style='margin: 0'>Classification: MNIST Project 1 - Introduction</p></td></tr><tr><td style='padding: 15px;'><p>5. MNIST Project 2 - SGDClassifiers</p><p style='margin: 0'>Classification: MNIST Project 2 - SGDClassifier</p></td></tr><tr><td style='padding: 15px;'><p>6. MNIST Project 3 - Performance Measures</p><p style='margin: 0'>Classification: MNIST Project 3 - Performance Measures</p></td></tr><tr><td style='padding: 15px;'><p>7. MNIST Project 4 - Confusion Matrix, Precision, Recall and F1 Score</p><p style='margin: 0'>Classification: MNIST Project 4 - Confusion Matrix, Precision, Recall and F1 Score</p></td></tr><tr><td style='padding: 15px;'><p>8. MNIST Project 5 - Precision and Recall Tradeoff</p><p style='margin: 0'>Classification: MNIST Project 5 - Precision and Recall Tradeoff</p></td></tr><tr><td style='padding: 15px;'><p>9. MNIST Project 6 - The ROC Curve</p><p style='margin: 0'>Classification: MNIST Project 6 - The ROC Curve</p></td></tr></tbody></table><br><h4>5. Support Vector Machine (SVM)</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Support Vector Machine (SVM): Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Support Vector Machine (SVM) Concepts</p><p style='margin: 0'>Support Vector Machine (SVM): Support Vector Machine (SVM) Concepts</p></td></tr><tr><td style='padding: 15px;'><p>3. Linear SVM Classification</p><p style='margin: 0'>Support Vector Machine (SVM): Linear SVM Classification</p></td></tr><tr><td style='padding: 15px;'><p>4. Polynomial Kernel</p><p style='margin: 0'>Support Vector Machine (SVM): Polynomial Kernel</p></td></tr><tr><td style='padding: 15px;'><p>5. Gaussian Radial Basis Function</p><p style='margin: 0'>Support Vector Machine (SVM): Gaussian Radial Basis Function</p></td></tr><tr><td style='padding: 15px;'><p>6. Support Vector Regression</p><p style='margin: 0'>Support Vector Machine (SVM): Support Vector Regression</p></td></tr><tr><td style='padding: 15px;'><p>7. Advantages and Disadvantages of SVM</p><p style='margin: 0'>Support Vector Machine (SVM): Advantages and Disadvantages of SVM</p></td></tr></tbody></table><br><h4>6. Tree</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Tree: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. What is Decision Tree</p><p style='margin: 0'>Tree: What is Decision Tree</p></td></tr><tr><td style='padding: 15px;'><p>3. Training a Decision Tree</p><p style='margin: 0'>Tree: Training a Decision Tree</p></td></tr><tr><td style='padding: 15px;'><p>4. Visualising a Decision Trees</p><p style='margin: 0'>Tree: Visualising a Decision Trees</p></td></tr><tr><td style='padding: 15px;'><p>5. Decision Tree Learning Algorithm</p><p style='margin: 0'>Tree: Decision Tree Learning Algorithm</p></td></tr><tr><td style='padding: 15px;'><p>6. Decision Tree Regression</p><p style='margin: 0'>Tree: Decision Tree Regression</p></td></tr><tr><td style='padding: 15px;'><p>7. Overfitting and Grid Search</p><p style='margin: 0'>Tree: Overfitting and Grid Search</p></td></tr><tr><td style='padding: 15px;'><p>8. Where to From Here</p><p style='margin: 0'>Tree: Where to From Here</p></td></tr><tr><td style='padding: 15px;'><p>9. Project HR - Loading and preprocesing data</p><p style='margin: 0'>Tree: Project HR - Loading and preprocesing data</p></td></tr><tr><td style='padding: 15px;'><p>10. Project HR - Modelling</p><p style='margin: 0'>Tree: Project HR - Modelling</p></td></tr></tbody></table><br><h4>7. Ensemble Machine Learning</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Ensemble Machine Learning: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Ensemble Learning Methods Introduction</p><p style='margin: 0'>Ensemble Machine Learning: Ensemble Learning Methods Introduction</p></td></tr><tr><td style='padding: 15px;'><p>3. Bagging Part 1</p><p style='margin: 0'>Ensemble Machine Learning: Bagging Part 1</p></td></tr><tr><td style='padding: 15px;'><p>4. Bagging Part 2</p><p style='margin: 0'>Ensemble Machine Learning: Bagging Part 2</p></td></tr><tr><td style='padding: 15px;'><p>5. Random Forests</p><p style='margin: 0'>Ensemble Machine Learning: Random Forests</p></td></tr><tr><td style='padding: 15px;'><p>6. Extra-Trees</p><p style='margin: 0'>Ensemble Machine Learning: Extra-Trees</p></td></tr><tr><td style='padding: 15px;'><p>7. AdaBoost</p><p style='margin: 0'>Ensemble Machine Learning: Decision Tree Regression</p></td></tr><tr><td style='padding: 15px;'><p>8. Gradient Boosting Machine</p><p style='margin: 0'>Ensemble Machine Learning: Gradient Boosting Machine</p></td></tr><tr><td style='padding: 15px;'><p>9. XGBoost</p><p style='margin: 0'>Ensemble Machine Learning: XGBoost</p></td></tr><tr><td style='padding: 15px;'><p>10. Project HR - Human Resources Analytics</p><p style='margin: 0'>Ensemble Machine Learning: Project HR - Human Resources Analytics</p></td></tr><tr><td style='padding: 15px;'><p>11. Ensemble of ensembles Part 1</p><p style='margin: 0'>Ensemble Machine Learning: Ensemble of ensembles Part 1</p></td></tr><tr><td style='padding: 15px;'><p>12. Ensemble of ensembles Part 2</p><p style='margin: 0'>Ensemble Machine Learning: Ensemble of ensembles Part 2</p></td></tr></tbody></table><br><h4>8. k-Nearest Neighbours (kNN)</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. kNN Introduction</p><p style='margin: 0'>K-Nearest Neighbours (kNN): kNN Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. kNN Concepts</p><p style='margin: 0'>K-Nearest Neighbours (kNN): kNN Concepts</p></td></tr><tr><td style='padding: 15px;'><p>3. kNN and Iris Dataset Demo</p><p style='margin: 0'>K-Nearest Neighbours (kNN): kNN and Iris Dataset Demo</p></td></tr><tr><td style='padding: 15px;'><p>4. Distance Metric</p><p style='margin: 0'>K-Nearest Neighbours (kNN): Distance Metric</p></td></tr><tr><td style='padding: 15px;'><p>5. Project Cancer Detection Part 1</p><p style='margin: 0'>K-Nearest Neighbours (kNN): Project Cancer Detection Part 1</p></td></tr><tr><td style='padding: 15px;'><p>6. Project Cancer Detection Part 2</p><p style='margin: 0'>K-Nearest Neighbours (kNN): Project Cancer Detection Part 2</p></td></tr></tbody></table><br><h4>9. Dimensionality Reduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Dimensionality Reduction: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Dimensionality Reduction Concept</p><p style='margin: 0'>Dimensionality Reduction: Dimensionality Reduction Concept</p></td></tr><tr><td style='padding: 15px;'><p>3. PCA Introduction</p><p style='margin: 0'>Dimensionality Reduction: PCA Introduction</p></td></tr><tr><td style='padding: 15px;'><p>4. Dimensionality Reduction Demo</p><p style='margin: 0'>Dimensionality Reduction: Dimensionality Reduction Demo</p></td></tr><tr><td style='padding: 15px;'><p>5. Project Wine 1: Dimensionality Reduction with PCA</p><p style='margin: 0'>Dimensionality Reduction: Project Wine 1: Dimensionality Reduction with PCA</p></td></tr><tr><td style='padding: 15px;'><p>6. Project Wine 2: Choosing the Number of Components</p><p style='margin: 0'>Dimensionality Reduction: Project Wine 2: Choosing the Number of Components</p></td></tr><tr><td style='padding: 15px;'><p>7. Kernel PCA</p><p style='margin: 0'>Dimensionality Reduction: Kernel PCA</p></td></tr><tr><td style='padding: 15px;'><p>8. Kernel PCA Demo</p><p style='margin: 0'>Dimensionality Reduction: Kernel PCA Demo</p></td></tr><tr><td style='padding: 15px;'><p>9. LDA & Comparison between LDA and PCA</p><p style='margin: 0'>Dimensionality Reduction: LDA &amp; Comparison between LDA and PCA</p></td></tr></tbody></table><br><h4>10. Unsupervised Learning: Clustering</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Unsupervised Learning: Clustering: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. Clustering Concepts</p><p style='margin: 0'>Unsupervised Learning: Clustering: Clustering Concepts</p></td></tr><tr><td style='padding: 15px;'><p>3. MLextend</p><p style='margin: 0'>Unsupervised Learning: Clustering: MLextend</p></td></tr><tr><td style='padding: 15px;'><p>4. Ward's Agglomerative Hierarchical Clustering</p><p style='margin: 0'>Unsupervised Learning: Clustering: Ward's Agglomerative Hierarchical Clustering</p></td></tr><tr><td style='padding: 15px;'><p>5. Truncating Dendrogram</p><p style='margin: 0'>Unsupervised Learning: Clustering: Truncating Dendrogram</p></td></tr><tr><td style='padding: 15px;'><p>6. k-Means Clustering</p><p style='margin: 0'>Unsupervised Learning: Clustering: k-Means Clustering</p></td></tr><tr><td style='padding: 15px;'><p>7. Elbow Method</p><p style='margin: 0'>Unsupervised Learning: Clustering: Elbow Method</p></td></tr><tr><td style='padding: 15px;'><p>8. Silhouette Analysis</p><p style='margin: 0'>Unsupervised Learning: Clustering: Silhouette Analysis</p></td></tr><tr><td style='padding: 15px;'><p>9. Mean Shift</p><p style='margin: 0'>Unsupervised Learning: Clustering: Mean Shift</p></td></tr></tbody></table>

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