Name: Data Analyst Training: Boost Your Career
Price: 279 GBP
Availability: InStock

<p>Feeling Stuck in Your Career? The Computer Science: Coding, C++, Python &amp; HTML (30 in 1) CPD Accredited Courses! Bundle is Your Skill-Building Solution. This exceptional collection of <strong>30 premium courses</strong> is designed to encourage growth and improve your career opportunities. Suited to meet different interests and goals, the Computer Science: Coding, C++, Python &amp; HTML bundle provides an engaging learning experience, helping you learn skills across various disciplines.</p><p>With Computer Science: Coding, C++, Python &amp; HTML (30 in 1) CPD Accredited Courses! Bundle, you'll have a personalised journey that aligns with your career goals and interests. This comprehensive package helps you confidently tackle new challenges, whether entering a new field or enhancing your existing knowledge. The Computer Science: Coding, C++, Python &amp; HTML bundle is your gateway to expanding your career options, increasing job demand, and enhancing your skill set.</p><p>By enrolling in this bundle, you'll receive complimentary PDF certificates for all courses, adding value to your resume at no extra cost. Develop key skills and achieve important progress in your career and personal development. Start your journey today and experience the transformative impact of the Computer Science: Coding, C++, Python &amp; HTML (30 in 1) CPD Accredited Courses! bundle on your job life and career growth!</p><p><strong>This Computer Science: Coding, C++, Python &amp; HTML (30 in 1) CPD Accredited Courses! Bundle Comprises the Following CPD Accredited Courses:</strong></p><ul><li><strong>Course 01</strong>: Basic C# Coding</li><li><strong>Course 02</strong>: C++ Programming for Absolute Beginners</li><li><strong>Course 03</strong>: Computer Science with Python</li><li><strong>Course 04</strong>: C++ Development: The Complete Coding Guide</li><li><strong>Course 05</strong>: Computer Vision By Using C++ and OpenCV with GPU support</li><li><strong>Course 06</strong>: jQuery: JavaScript and AJAX Coding Bible</li><li><strong>Course 07</strong>: Ultimate PHP &amp; MySQL Web Development &amp; OOP Coding</li><li><strong>Course 08</strong>: Coding with Scratch</li><li><strong>Course 09</strong>: Learn CSS Coding from Scratch</li><li><strong>Course 10</strong>: Kotlin Masterclass Programming Course: Android Coding Bible</li><li><strong>Course 11</strong>: jQuery Masterclass Course: JavaScript and AJAX Coding Bible</li><li><strong>Course 12</strong>: Basic HTML 5</li><li><strong>Course 13</strong>: HTML Web Development Crash Course</li><li><strong>Course 14</strong>: Creative Web Design with HTML5, CSS3 and Bootstrap</li><li><strong>Course 15</strong>: Web Design for Beginners: Build Websites in HTML &amp; CSS</li><li><strong>Course 16</strong>: Python Intermediate Training</li><li><strong>Course 17</strong>: Learn Python, JavaScript, and Microsoft SQL for Data Science</li><li><strong>Course 18</strong>: Spatial Data Visualisation and Machine Learning in Python</li><li><strong>Course 19</strong>: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li><strong>Course 20</strong>: Python Programming Bible | Networking, GUI, Email, XML, CGI</li><li><strong>Course 21</strong>: Deep Learning &amp; Neural Networks Python - Keras</li><li><strong>Course 22</strong>: The Complete Python 3 Course: Beginner to Advanced!</li><li><strong>Course 23</strong>: Machine Learning with Python Course</li><li><strong>Course 24</strong>: Python Advanced Training</li><li><strong>Course 25</strong>: Cloud Computing / CompTIA Cloud+ (CV0-002)</li><li><strong>Course 26</strong>: CompTIA IT Fundamentals ITF+ (FCO-U61)</li><li><strong>Course 27</strong>: Learn Ethical Hacking From A-Z: Beginner To Expert</li><li><strong>Course 28</strong>: Computer Simulation of Realistic Mathematical Models</li><li><strong>Course 29</strong>: Computer Hacking Forensic Investigator</li><li><strong>Course 30</strong>: Career Development Plan Fundamentals</li></ul><p><strong>What will make you stand out?</strong></p><p>Upon completion of this online Computer Science: Coding, C++, Python &amp; HTML (30 in 1) CPD Accredited Courses! Bundle, you will gain the following:</p><ul><li>CPD QS Accredited Proficiency with this Computer Science: Coding, C++, Python &amp; HTML Bundle</li><li>After successfully completing the Computer Science: Coding, C++, Python &amp; HTML bundle, you will receive a FREE PDF Certificate from REED as evidence of your newly acquired abilities.</li><li>Lifetime access to the whole collection of learning materials of this Computer Science: Coding, C++, Python &amp; HTML Bundle</li><li>The online test with immediate results</li><li>You can study and complete the Computer Science: Coding, C++, Python &amp; HTML bundle at your own pace.</li><li>Study for the Computer Science: Coding, C++, Python &amp; HTML bundle using any internet-connected device, such as a computer, tablet, or mobile device.</li></ul><p>The Computer Science: Coding, C++, Python &amp; HTML (30 in 1) CPD Accredited Courses! bundle is a premier learning resource, with each course module holding respected CPD accreditation, symbolising exceptional quality. The content is packed with knowledge and is regularly updated to ensure it remains relevant. This bundle offers not just education but a constantly improving learning experience designed to enrich both your personal and professional development.</p><p>Advance the future of learning with the Computer Science: Coding, C++, Python &amp; HTML bundle, a comprehensive, complete collection of 30 courses. Each course in the Computer Science: Coding, C++, Python &amp; HTML bundle has been handpicked by our experts to provide a broad range of learning opportunities. Together, these modules form an important and well-rounded learning experience.</p><p>Our mission is to deliver high-quality, accessible education for everyone. Whether you are starting your career, switching industries, or enhancing your professional skills, the Computer Science: Coding, C++, Python &amp; HTML bundle offers the flexibility and convenience to learn at your own pace. Make the Computer Science: Coding, C++, Python &amp; HTML package your trusted partner in your lifelong learning journey.</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>The Computer Science: Coding, C++, Python &amp; HTML (30 in 1) CPD Accredited Courses! is perfect for:</p><ul><li>Expand your knowledge and skillset for a fulfilling career with the Computer Science: Coding, C++, Python &amp; HTML bundle.</li><li>Become a more valuable professional by earning CPD certification and mastering in-demand skills with the Computer Science: Coding, C++, Python &amp; HTML bundle.</li><li>Discover your passion or explore new career options with the diverse learning opportunities in the Computer Science: Coding, C++, Python &amp; HTML bundle.</li><li>Learn on your schedule, in the comfort of your home - the Computer Science: Coding, C++, Python &amp; HTML bundle offers ultimate flexibility for busy individuals.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You are warmly invited to register for this bundle. Please be aware that no formal entry requirements or qualifications are necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Gain a wide range of skills across various fields, improve your problem-solving capabilities, and keep current with industry trends. Perfect for those aiming for career advancement, exploring a new professional direction, or pursuing personal growth. Begin your journey with the Computer Science: Coding, C++, Python &amp; HTML bundle.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Certificates</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Compliance Central

Computer Science: Coding, C++ , Python & HTML (30 in 1) CPD Accredited Courses!

General Admission

<p><strong>***24 Hour Limited Time Flash Sale***</strong></p><p><strong> </strong><strong>Data Visualisation Professional - CPD Certified </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 Data Visualisation Professional - CPD Certified 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 Data Visualisation Professional - CPD Certified 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 Data Visualisation Professional - CPD Certified 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 Data Visualisation Professional - CPD Certified Career Bundle:</strong></p><ul><li> Course 01: Master JavaScript with Data Visualization</li><li> Course 02: SQL for Data Science, Data Analytics and Data Visualization</li><li> Course 03: Spatial Data Visualization and Machine Learning in Python</li><li> Course 04: Data Analysis</li><li> Course 05: Excel Data Analysis</li><li> Course 06: Excel Pivot Tables, Pivot Charts, Slicers, and Timelines</li><li> Course 07: Python Programming Bible</li><li> Course 08: Python Data Science with Numpy, Pandas and Matplotlib</li><li> Course 09: Data Science &amp; Machine Learning with Python</li><li> Course 10: Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li> Course 11: R Programming for Data Science</li><li> Course 12: Quick Data Science Approach from Scratch</li><li> Course 13: Mastering SQL Programming</li><li> Course 14: Learn Python, JavaScript, and Microsoft SQL for Data science</li><li> Course 15: Web Scraping and Mapping Dam Levels in Python and Leaflet</li><li> Course 16: Business Data Analysis</li><li> Course 17: Business Intelligence and Data Mining Diploma</li><li> Course 18: Google Data Studio: Data Analytics</li><li> Course 19: Google Analytics for Everyone</li><li> Course 20: Big Data Analytics with PySpark Tableau Desktop and MongoDB</li><li> Course 21: Big Data Analytics with PySpark Power BI and MongoDB</li><li> Course 22: Introduction to Data Analytics with Tableau</li><li> Course 23: Microsoft Power BI - Master Power BI in 90 Minutes!</li><li> Course 24: PowerBI Formulas</li><li> Course 25: Develop Big Data Pipelines with R &amp; Sparklyr &amp; Tableau</li><li> Course 26: Develop Big Data Pipelines with R, Sparklyr &amp; Power BI</li><li> Course 27: Microsoft Access Tables and Queries</li><li> Course 28: Statistical Analysis</li><li> Course 29: Research Methods in Business</li><li> Course 30: Customer Analytics Training</li></ul><p>With Data Visualisation Professional - CPD Certified, 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. And with 24/7 tutor support, you'll never feel alone in your journey, whether you're a seasoned professional or a beginner.</p><p>Don't let this opportunity pass you by. Enrol in Data Visualisation Professional - CPD Certified today and take the first step towards achieving your goals and dreams.</p><p><strong>Why buy this Data Visualisation Professional - CPD Certified?</strong></p><ul><li><strong>Free CPD Accredited Certificate</strong> upon completion of Data Visualisation Professional - CPD Certified</li><li>Get <strong>a free student ID card</strong> with Data Visualisation Professional - CPD Certified</li><li><strong>Lifetime access</strong> to the Data Visualisation Professional - CPD Certified course materials</li><li>Get instant access to this Data Visualisation Professional - CPD Certified course</li><li>Learn Data Visualisation Professional - CPD Certified from anywhere in the world</li><li>24/7 tutor support with the Data Visualisation Professional - CPD Certified course.</li></ul> <p><strong>Start your learning journey straightaway with our Data Visualisation Professional - CPD Certified Training!</strong></p><p>Data Visualisation Professional - CPD Certified 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 Data Visualisation Professional - CPD Certified 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 Data Visualisation Professional - CPD Certified course. After passing the Data Visualisation Professional - CPD Certified 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 Data Visualisation Professional - CPD Certified course is ideal for:</strong></p><ul><li>Students seeking mastery in Data Visualisation Professional - CPD Certified</li><li>Professionals seeking to enhance Data Visualisation Professional - CPD Certified skills</li><li>Individuals looking for a Data Visualisation Professional - CPD Certified-related career.</li><li>Anyone passionate about Data Visualisation Professional - CPD Certified</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This <strong>Data Visualisation Professional - CPD Certified </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>After the assessment, you will be ready for countless job opportunities. Some of them are-</p><ul><li>Business Analyst</li><li>Business Intelligence Analyst</li><li>Analytics Manager</li><li>Data Analyst</li><li>Data Scientist</li></ul><p>However, in the growing market of the UK, these professionals are expected to earn between <strong>£25k to £80k</strong> yearly on average.</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 <strong>international student</strong>, then you have to pay an additional <strong>10 GBP</strong> for each certificate as an international delivery charge.</p></div>

                        </div>

Academy for Health and Fitness

Data Visualisation Professional - CPD Certified

<p>Tired of lost profits and missed opportunities? Imagine deciphering customer behaviour like a master codebreaker, predicting trends with laser accuracy, and turning data into a goldmine for your sales. Data Modelling empowers you to do just that.</p><p>UK retail alone saw a staggering £18 billion lost to poor data analysis in 2022. But the flip side? Companies embracing data-driven strategies saw a 6% average revenue boost. It's no longer a "nice-to-have" - it's the difference between thriving and surviving in today's dynamic market.</p><p>Stop guessing and start knowing. This Data Modelling course equips you with the skills to transform raw data into actionable insights. Learn to build powerful models, uncover hidden patterns, and forecast future sales with confidence. Take control of your sales destiny - enrol now and unlock the power of data.</p><p><strong>Learning Outcomes:</strong></p><ul><li>Execute robust Data Analysis using Excel for insightful decision-making.</li><li>Develop and administer MySQL databases for efficient data management.</li><li>Create impactful visualisations with Tableau for effective data communication.</li><li>Master Python and R for cutting-edge Data Science and Machine Learning.</li><li>Harness the power of Google BigQuery &amp; Cloud for scalable data engineering solutions.</li></ul><p>Embark on a transformative journey through the world of data, from fundamental analysis to advanced engineering. This diploma encompasses Data Analysis, Modelling, and Database Development, providing a holistic approach to data mastery. Dive into the intricacies of R Programming, Statistics, and Google Cloud, equipping yourself with skills that are highly sought after in today's data-driven landscape. Enroll now to stay ahead in the dynamic field of data!</p><p>This CPDQS Accredited Data Modelling Made Easy Bundle consists of these following 11 courses:</p><ul><li>Diploma in Data Analysis Fundamentals</li><li>Data Analysis In Excel</li><li>Data Entry Administrator Training</li><li>Diploma in Data Analytics with Tableau</li><li>MySQL Database Development</li><li>Data Science &amp; Machine Learning with Python</li><li>Business Data Analysis</li><li>Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li>R Programming for Data Science</li><li>Easy to Advanced Data Structures</li><li>Data Engineering with Google BigQuery &amp; Google Cloud</li></ul><p><strong>Certification</strong><br />Once you have finished the course, you will be eligible to apply for a CPD QS accredited certificate as proof of your new skills and your continued professional development. Certificates are available as PDF for £9, or you can request a hard copy to be sent in the post for £15.<br /></p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        35 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>Ideal for aspiring data analysts, professionals seeking career advancement, and tech enthusiasts.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p> Open to all! No formal prerequisites. Embrace the world of data without barriers.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Analyst - £30,000 to £45,000</li><li>Database Developer - £35,000 to £50,000</li><li>Machine Learning Engineer - £45,000 to £70,000</li><li>Business Intelligence Analyst - £40,000 to £55,000</li><li>Data Engineer - £50,000 to £75,000</li></ul>
                        </div>

One Education

Data Modelling Made Easy - CPDQS Accredited Course

<p>Take the initial steps toward a successful long-term career by studying the<strong> IT </strong>package online with <strong>StudyHub </strong>through our online learning platform. After completing extensive research, we designed this customised IT course to ease your journey toward your goal. The IT course covers all of the latest information to keep you ahead of the job market and prepare you for the next step.</p><p>The IT bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass.</p><p><strong>This IT Training Bundle consists the following career oriented courses:</strong></p><ul><li><strong> Course 01: </strong>IT Support Technician</li><li><strong> Course 02: </strong>Network Security and Risk Management</li><li><strong> Course 03: </strong>CompTIA Network</li><li><strong> Course 04: </strong>Information Management</li><li><strong> Course 05: </strong>Web Application Penetration Testing Course</li><li><strong> Course 06: </strong>CompTIA Cloud+ (CV0-002)</li><li><strong> Course 07: </strong>Learn Ethical Hacking From A-Z: Beginner To Expert</li><li><strong> Course 08: </strong>Computer Operating System and Troubleshooting</li><li><strong> Course 09: </strong>Building Your Own Computer Course</li><li><strong> Course 10: </strong>It: Ethical Hacking, IT Security and IT Cyber Attacking</li><li><strong> Course 11: </strong>SQL Database Administrator</li><li><strong> Course 12: </strong>MS Word Essentials - The Complete Word Course - Level 3</li><li><strong> Course 13: </strong>Data Protection (GDPR) Practitioner</li><li><strong> Course 14: </strong>Website Hacking From Scratch</li><li><strong> Course 15: </strong>Diploma in Front-End Web Development (HTML, CSS, &amp; Bootstrap)</li><li><strong> Course 16: </strong>Data Science and Visualisation with Machine Learning</li><li><strong> Course 17: </strong>SQL For Data Analytics &amp; Database Development</li><li><strong> Course 18: </strong>PLC Programming Diploma</li><li><strong> Course 19: </strong>Cyber Security Incident Handling and Incident Response</li><li><strong> Course 20:</strong> Cyber Security Law</li><li><strong> Course 21: </strong>C# (C-Sharp)</li><li><strong> Course 22: </strong>Web Design (HTML, CSS, Bootstrap) Complete Course</li><li><strong> Course 23: </strong>Python Course</li><li><strong> Course 24: </strong>JavaScript</li><li><strong> Course 25: </strong>ASP.Net MVC and Entity Framework Course</li><li><strong> Course 26: </strong>Learn Spring &amp; Angular Material with a Full Web Application</li><li><strong> Course 27: </strong>Coding Essentials - Javascript, ASP. Net, C# - Bonus HTML</li><li><strong> Course 28: </strong>Project on Deep Learning - Artificial Neural Network (ANNs)</li><li><strong> Course 29: </strong>Build Progressive Web Apps with Angular</li><li><strong> Course 30: </strong>Microsoft SQL Server Development for Everyone!</li><li><strong> Course 31:</strong> Building Big Data Pipelines with PySpark MongoDB and Bokeh</li><li><strong> Course 32: </strong>Microsoft Azure Machine Learning</li><li><strong> Course 33: </strong>Linux Basics</li><li><strong> Course 34: </strong>Linux File Management System</li><li><strong> Course 35: </strong>C Programming Language for Beginners on Linux</li><li><strong> Course 36: </strong>Linux Security and Hardening</li><li><strong> Course 37: </strong>Linux Shell Scripting</li><li><strong> Course 38: </strong>Learn Ethical Hacking From A-Z: Beginner To Expert</li><li><strong> Course 39: </strong>Securing an Ubuntu Linux Server against Hackers Masterclass</li><li><strong> Course 40: </strong>Python 3 Programming</li></ul> <p>The <strong>IT Training</strong> Bundle has been prepared by focusing largely on career readiness.</p><p>The IT course has been prepared by focusing largely on career readiness. It has been designed by our IT 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 with IT, if it's required by any learners.</p><p><strong>Certification</strong></p><p>After studying the complete training, you will be able to participate in the course assessment, which is included in the course. After completing the assessment, you can claim all courses pdf certificates for free. Hard Copy certificates need to be ordered at an additional cost of •8.</p> <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>This IT Training course is suitable for -</p><ul><li>Students</li><li>Recent graduates</li><li>Job Seekers</li><li>further progress towards NCFE Level 3 Diploma in Skills for Business: IT</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>There is no formal qualification needed for this IT Training course.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>You will be able to achieve a lucrative career because this IT Training Bundle includes various courses as a bonus.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Studyhub UK

Certificate in Further Education & Training (Cert Ed)

IT Certifications

IT Skills

Certificate in Education & Training (CET)

Trainers Course

ICDL (International Certification of Digital Literacy)

Level 3 Diploma in Skills for Business: IT - CPD Certified

<strong>Data scraping is used to get the data available on different websites and APIs. This also involves automating the web flows to extract the data from different web pages. Data Scraping and Data Mining with Python is a well-designed course for beginners to develop a solid groundwork for the skills necessary.</strong>
        <p>Data scraping is the technique of extracting data from the Internet. The course Data Scraping and Data Mining from Beginner to Professional is crafted to cover topics that result in the development of the most in-demand skills in the workplace. These topics will help you understand the concepts and methodologies with regard to Python. The course is easy to understand, imaginative and descriptive, comprehensive, practical with live coding, full of quizzes with solutions, rich with state-of-the-art and updated knowledge of this field.

This course is designed for beginners. We'll spend sufficient time on the fundamentals. Then, we will gradually go far deep with a lot of practical implementations where every step will be explained in detail.

As this course is essentially a compilation of all the basics, you will move ahead at a steady rate. You will experience more than what you have learned. Most of these activities are designed to get you up and running with implementations.

The four hands-on projects included are the most important part of this course. These projects allow you to experiment for yourself with trial and error. You will learn from your mistakes. Importantly, you will understand the potential gaps that may exist between theory and practice.

Code bundles are available here: https://github.com/PacktPublishing/Data-Scraping-and-Data-Mining-from-Beginner-to-Pro-with-Python</p>
        <h2>What You Will Learn</h2><p>Understand the difference between synchronous and asynchronous requests<br>Apply BS4 for parsing the response data from the server<br>Explore the different tools that are used for data scraping; namely, Requests, BS4, Scrapy, Selenium<br>Understand BS4 parser functions for getting the data out of the HTML<br>Learn to use Scrapy to write the spiders for crawling websites and extracting data<br>Learn to use Selenium to understand the automation and control of web flows</p>
        <h2>Audience</h2><p>This course is for people who are beginners and absolutely new to data scraping and for individuals who want to make smart solutions and learn data scraping with real data using Python.<br><br>It is also useful for data scientists, machine learning experts, drop shippers who are interested in learning data scraping along with its implementation in realistic projects.</p>
        <h2>Approach</h2><p>The entire course follows a practical hands-on approach ensuring that you can practice and understand all core concepts. The course has an interactive learning experience with practice exercises and assignments at the end of every concept along with solutions. They will assess and further build your learning based on the previous data scraping and data mining concepts and methods.</p>
        <h2>Key Features</h2><p>Relate the concepts and practical aspects of data scraping with real-world problems * Know the theory and practical aspects of data scraping concepts * Implement any project from scratch that requires data scraping knowledge</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Data-Scraping-and-Data-Mining-from-Beginner-to-Pro-with-Python</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</h4><p></p><br><h4>2. Requests</h4><p></p><br><h4>3. Beautiful Soap 4(BS4)</h4><p></p><br><h4>4. CSS Selectors</h4><p></p><br><h4>5. Scrapy</h4><p></p><br><h4>6. Scrapy Project</h4><p></p><br><h4>7. Selenium</h4><p></p><br><h4>8. Project Selenium</h4><p></p>

Packt

Data Mining

Selenium

Python

Data scraping is used to get the data available on different websites and APIs. This also involves automating the web flows to extract the data from different web pages. Data Scraping and Data Mining with Python is a well-designed course for beginners to develop a solid groundwork for the skills necessary.

Data Scraping and Data Mining from Beginner to Pro with Python

<p>Feeling Stuck in Your Career? The Data Analyst (Data Analytics) Bundle is Your Skill-Building Solution. This exceptional collection of <strong>30 premium courses</strong> is designed to encourage growth and improve your career opportunities. Suited to meet different interests and goals, the Data Analyst-(Data Analytics) bundle provides an engaging learning experience, helping you learn skills across various disciplines.</p><p>With the Data Analyst (Data Analytics) Bundle, you'll have a personalised journey that aligns with your career goals and interests. This comprehensive package helps you confidently tackle new challenges, whether entering a new field or enhancing your existing knowledge. The Data Analyst-(Data Analytics) bundle is your gateway to expanding your career options, increasing job demand, and enhancing your skill set.</p><p>By enrolling in this bundle, you'll receive complimentary PDF certificates for all courses, adding value to your resume at no extra cost. Develop key skills and achieve important progress in your career and personal development. Start your journey today and experience the transformative impact of the Data Analyst-(Data Analytics) bundle on your job life and career growth!</p><p><strong>This Data Analyst (Data Analytics) </strong><strong>Bundle Comprises the Following CPD Accredited Courses:</strong></p><ul><li><strong>Course 01</strong>: Basic Data Analysis</li><li><strong>Course 02</strong>: Business Data Analysis</li><li><strong>Course 03</strong>: Introduction to Data Analytics with Tableau</li><li><strong>Course 04</strong>: Google Data Studio: Data Analytics</li><li><strong>Course 05</strong>: SQL Database Basics for Everyone</li><li><strong>Course 06</strong>: R Programming for Data Science</li><li><strong>Course 07</strong>: 2021 Data Science &amp; Machine Learning with R from A-Z</li><li><strong>Course 08</strong>: Learn Python, JavaScript, and Microsoft SQL for Data Science</li><li><strong>Course 09</strong>: Spatial Data Visualisation and Machine Learning in Python</li><li><strong>Course 10</strong>: Building Big Data Pipelines with PySpark MongoDB and Bokeh</li><li><strong>Course 11</strong>: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li><strong>Course 12</strong>: Clinical Data Management with SAS Programming</li><li><strong>Course 13</strong>: Certificate in Data Entry and Management</li><li><strong>Course 14</strong>: Quick Data Science Approach from Scratch</li><li><strong>Course 15</strong>: Web Mapping and Data Visualizations</li><li><strong>Course 16</strong>: Programming AutoCAD with SQL Server Database Using C#</li><li><strong>Course 17</strong>: Big Data Analytics with PySpark Power BI and MongoDB</li><li><strong>Course 18</strong>: Develop Big Data Pipelines with R &amp; Sparklyr &amp; Tableau</li><li><strong>Course 19</strong>: Develop Big Data Pipelines with R, Sparklyr &amp; Power BI</li><li><strong>Course 20</strong>: Data Center Training Essentials: Power &amp; Electrical</li><li><strong>Course 21</strong>: Business Intelligence and Data Mining</li><li><strong>Course 22</strong>: Set Menu Prices for your restaurant using data</li><li><strong>Course 23</strong>: Data Analysis In Excel</li><li><strong>Course 24</strong>: Data Protection</li><li><strong>Course 25</strong>: Reporting and Data</li><li><strong>Course 26</strong>: Career Development Plan Fundamentals</li><li><strong>Course 27</strong>: CV Writing and Job Searching</li><li><strong>Course 28</strong>: Learn to Level Up Your Leadership</li><li><strong>Course 29</strong>: Networking Skills for Personal Success</li><li><strong>Course 30</strong>: Ace Your Presentations: Public Speaking Masterclass</li></ul><p><strong>What will make you stand out?</strong></p><p>Upon completion of this online Data Analyst (Data Analytics) Bundle, you will gain the following:</p><ul><li>CPD QS Accredited Proficiency with this Data Analyst-(Data Analytics) bundle</li><li>After successfully completing the Data Analyst-(Data Analytics) bundle, you will receive a FREE PDF Certificate from REED as evidence of your newly acquired abilities.</li><li>Lifetime access to the whole collection of learning materials of this Data Analyst-(Data Analytics) bundle</li><li>The online test with immediate results</li><li>You can study and complete the Data Analyst-(Data Analytics) bundle at your own pace.</li><li>Study for the Data Analyst-(Data Analytics) bundle using any internet-connected device, such as a computer, tablet, or mobile device.</li></ul><p>The Data Analyst (Data Analytics) bundle is a premier learning resource, with each course module holding respected CPD accreditation, symbolising exceptional quality. The content is packed with knowledge and is regularly updated to ensure it remains relevant. This bundle offers not just education but a constantly improving learning experience designed to enrich both your personal and professional development.</p><p>Advance the future of learning with the Data Analyst-(Data Analytics) <strong>bundle</strong>, a comprehensive, complete collection of 30 courses. Each course in the Data Analyst-(Data Analytics) bundle has been handpicked by our experts to provide a broad range of learning opportunities. Together, these modules form an important and well-rounded learning experience.</p><p>Our mission is to deliver high-quality, accessible education for everyone. Whether you are starting your career, switching industries, or enhancing your professional skills, the Data Analyst-(Data Analytics) bundle offers the flexibility and convenience to learn at your own pace. Make the Data Analyst-(Data Analytics) package your trusted partner in your lifelong learning journey.</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>The Data Analyst (Data Analytics) bundle is perfect for:</p><ul><li>Expand your knowledge and skillset for a fulfilling career with the Data Analyst-(Data Analytics) bundle.</li><li>Become a more valuable professional by earning CPD certification and mastering in-demand skills with the Data Analyst-(Data Analytics) bundle.</li><li>Discover your passion or explore new career options with the diverse learning opportunities in the Data Analyst-(Data Analytics) bundle.</li><li>Learn on your schedule, in the comfort of your home - the Data Analyst-(Data Analytics) bundle offers ultimate flexibility for busy individuals.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You are warmly invited to register for this bundle. Please be aware that no formal entry requirements or qualifications are necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Gain a wide range of skills across various fields, improve your problem-solving capabilities, and keep current with industry trends. Perfect for those aiming for career advancement, exploring a new professional direction, or pursuing personal growth. Begin your journey with the Data Analyst (Data Analytics) bundle.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Certificates</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Data Analyst (Data Analytics) - 30 CPD Courses!

<p>Do you want to prepare for your dream job but strive hard to find the right courses? Then, stop worrying, for our strategically modified<strong> Basics of Data Science</strong> bundle will keep you up to date with the relevant knowledge and most recent matters of this emerging field. So, invest your money and effort in our <strong>40 </strong> course mega bundle that will exceed your expectations within your budget.</p> <p>The<strong> Basics of Data Science</strong> related fields are thriving across the UK, and recruiters are hiring the most knowledgeable and proficient candidates. It's a demanding field with magnitudes of lucrative choices. If you need more guidance to specialise in this area and need help knowing where to start, then <strong>StudyHub </strong> proposes a preparatory bundle. This comprehensive <strong>Basics of Data Science</strong> bundle will help you build a solid foundation to become a proficient worker in the sector.</p> <p><strong>This Basics of Data Science Bundle consists of the following</strong><strong> 30 </strong><strong>CPD Accredited Premium courses - </strong></p> <ul> <li>Course 1: Business Intelligence and Data Mining</li><li>Course 2: Diploma in Data Analysis Fundamentals</li><li>Course 3: Google Data Studio: Data Analytics</li><li>Course 4: Statistics</li><li>Course 5: Statistical Analysis</li><li>Course 6: Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li>Course 7: Quick Data Science Approach from Scratch</li><li>Course 8: SAS Programming Basic to Advanced</li><li>Course 9: R Programming for Data Science</li><li>Course 10: Python Data Science</li><li>Course 11: Data Science &amp; Machine Learning with Python</li><li>Course 12: Microsoft Power BI - Master Power BI in 90 Minutes!</li><li>Course 13: PowerBI Formulas</li><li>Course 14: Excel Data Analysis</li><li>Course 15: Excel Data Tools and Data Management</li><li>Course 16: Master JavaScript with Data Visualization</li><li>Course 17: Research Methods in Business</li><li>Course 18: Fundamentals of Business Analysis</li><li>Course 19: Financial Analysis</li><li>Course 20: Financial Modeling Using Excel</li><li>Course 21: Investment Analyst</li><li>Course 22: Technical Analysis Masterclass for Trading &amp; Investing</li><li>Course 23: Understanding Financial Statements and Analysis</li><li>Course 24: Strategic Planning and Analysis for Marketing</li><li>Course 25: Stock Trading Analysis with Volume Trading</li><li>Course 26: Time Management Training - Online Course</li><li>Course 27: Complete Communication Skills Master Class for Life</li><li>Course 28: Public Speaking</li><li>Course 29: Minute Taking Executive Training</li><li>Course 30: Receptionist Skills</li></ul> <p><strong>10 </strong><strong>Extraordinary Career Oriented courses that will assist you in reimagining your thriving techniques-</strong></p> <ul> <li>Course 1: Career Development Plan Fundamentals</li><li>Course 2: CV Writing and Job Searching</li><li>Course 3: Interview Skills: Ace the Interview</li><li>Course 4: Video Job Interview for Job Seekers</li><li>Course 5: Create a Professional LinkedIn Profile</li><li>Course 6: Business English Perfection Course</li><li>Course 7: Networking Skills for Personal Success</li><li>Course 8: Boost Your Confidence and Self-Esteem</li><li>Course 9: Public Speaking Training</li><li>Course 10: Learn to Fight Procrastination</li></ul> <p><strong>Learning Outcome</strong></p> <p><strong>This tailor-made </strong><strong>Basics of Data Science</strong><strong> bundle will allow you to-</strong></p> <ul> <li>Uncover your skills and aptitudes to break new ground in the related fields</li><li>Deep dive into the fundamental knowledge</li><li>Acquire some hard and soft skills in this area</li><li>Gain some transferable skills to elevate your performance</li><li>Maintain good report with your clients and staff</li><li>Gain necessary office skills and be tech savvy utilising relevant software</li><li>Keep records of your work and make a report</li><li>Know the regulations around this area</li><li>Reinforce your career with specific knowledge of this field</li><li>Know your legal and ethical responsibility as a professional in the related field</li></ul> <p>This Basics of Data Science Bundle resources were created with the help of industry experts, and all subject-related information is kept updated on a regular basis to avoid learners from falling behind on the latest developments.</p> <p><strong>Certification</strong></p> <p>After studying the complete training you will be able to take the assessment. After successfully passing the assessment you will be able to claim all courses pdf certificates and <strong>1 hardcopy certificate for the Title Course completely free</strong>. Other Hard Copy certificates need to be ordered at an additional cost of •8.</p> <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>Ambitious learners who want to strengthen their CV for their desired job should take advantage of the Basics of Data Science bundle! This bundle is also ideal for professionals looking for career advancement.</p> 
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                             <p>To participate in this course, all you need is -</p> <ul> <li>A smart device</li><li>A secure internet connection</li><li>And a keen interest in Basics of Data Science</li></ul> 
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                             <p>Upon completing this essential Bundle, you will discover a new world of endless possibilities. These courses will help you to get a cut above the rest and allow you to be more efficient in the relevant fields.</p> 
                        </div>

Business Analytics & Intelligence

Big Data Analytics

Data Science

Professional Skills Course (PSC)

Data Skills

Digital Skills

Basics of Data Science

<p>Do you want to prepare for your dream job but strive hard to find the right courses? Then, stop worrying, for our strategically modified<strong> Data Analysis and Data Tools</strong> bundle will keep you up to date with the relevant knowledge and most recent matters of this emerging field. So, invest your money and effort in our <strong> 30 </strong>course mega bundle that will exceed your expectations within your budget.</p><p>The<strong> Data Analysis and Data Tools</strong> related fields are thriving across the UK, and recruiters are hiring the most knowledgeable and proficient candidates. It's a demanding field with magnitudes of lucrative choices. If you need more guidance to specialise in this area and need help knowing where to start, then <strong>StudyHub </strong>proposes a preparatory bundle. This comprehensive <strong>Data Analysis and Data Tools</strong> bundle will help you build a solid foundation to become a proficient worker in the sector.</p><p><strong>This Data Analysis and Data Tools Bundle consists of the following</strong><strong> 25 </strong><strong>CPD Accredited Premium courses - </strong></p><ul><li>Course 1: Basic Data Analysis</li><li>Course 2: Excel Data Analysis</li><li>Course 3: 2021 Python Programming From A-Z: Beginner To Expert</li><li>Course 4: Python Data Science with Numpy, Pandas and Matplotlib</li><li>Course 5: 2021 Data Science &amp; Machine Learning with R from A-Z</li><li>Course 6: Mastering SQL Programming</li><li>Course 7: Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li>Course 8: Quick Data Science Approach from Scratch</li><li>Course 9: R Programming for Data Science</li><li>Course 10: Learn Python, JavaScript, and Microsoft SQL for Data science</li><li>Course 11: Google Data Studio: Data Analytics</li><li>Course 12: Introduction to Excel Data Tools and Data Management</li><li>Course 13: Data Center Training Essentials: General Introduction</li><li>Course 14: Web Scraping and Mapping Dam Levels in Python and Leaflet</li><li>Course 15: Microsoft Power BI - Master Power BI in 90 Minutes!</li><li>Course 16: PowerBI Formulas</li><li>Course 17: Business Intelligence and Data Mining</li><li>Course 18: Financial Ratio Analysis for Business Decisions</li><li>Course 19: Research Methods in Business</li><li>Course 20: Cyber Security Incident Handling and Incident Response</li><li>Course 21: Microsoft Azure 2017</li><li>Course 22: AZ-104: Microsoft Azure Administrator</li><li>Course 23: Microsoft Azure Cloud Concepts</li><li>Course 24: Advanced Excel Analytics</li><li>Course 25: Microsoft Access Tables and Queries</li></ul><p><strong>5 </strong><strong>Extraordinary Career Oriented courses that will assist you in reimagining your thriving techniques-</strong></p><ul><li>Course 1:Career Development Plan Fundamentals</li><li>Course 2:CV Writing and Job Searching</li><li>Course 3:Interview Skills: Ace the Interview</li><li>Course 4:Video Job Interview for Job Seekers</li><li>Course 5:Create a Professional LinkedIn Profile</li></ul><p><strong>Learning Outcome</strong></p><p><strong>This tailor-made </strong><strong>Data Analysis and Data Tools</strong><strong> bundle will allow you to-</strong></p><ul><li>Uncover your skills and aptitudes to break new ground in the related fields</li><li>Deep dive into the fundamental knowledge</li><li>Acquire some hard and soft skills in this area</li><li>Gain some transferable skills to elevate your performance</li><li>Maintain good report with your clients and staff</li><li>Gain necessary office skills and be tech savvy utilising relevant software</li><li>Keep records of your work and make a report</li><li>Know the regulations around this area</li><li>Reinforce your career with specific knowledge of this field</li><li>Know your legal and ethical responsibility as a professional in the related field</li></ul> <p>This Data Analysis and Data Tools Bundle resources were created with the help of industry experts, and all subject-related information is kept updated on a regular basis to avoid learners from falling behind on the latest developments.</p><p><strong>Certification</strong></p><p>After studying the complete training you will be able to take the assessment. After successfully passing the assessment you will be able to claim all courses pdf certificates and <strong>1 hardcopy certificate for the Title Course completely free</strong>. Other Hard Copy certificates need to be ordered at an additional cost of •8.</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>Ambitious learners who want to strengthen their CV for their desired job should take advantage of the Data Analysis and Data Tools bundle! This bundle is also ideal for professionals looking for career advancement.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>To participate in this course, all you need is -</p><ul><li>A smart device</li><li>A secure internet connection</li><li>And a keen interest in Data Analysis and Data Tools</li></ul>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Upon completing this essential Bundle, you will discover a new world of endless possibilities. These courses will help you to get a cut above the rest and allow you to be more efficient in the relevant fields.</p>
                        </div>

AWS Certified Cloud Practitioner

Certified in Data Protection (CDP)

Continuous Professional Development (CPD)

CPD Certified Data Visualization Professional

<p>Do you want to prepare for your dream job but strive hard to find the right courses? Then, stop worrying, for our strategically modified<strong> Data Analyst Training: Boost Your Career</strong> bundle will keep you up to date with the relevant knowledge and most recent matters of this emerging field. So, invest your money and effort in our <strong>33</strong> course mega bundle that will exceed your expectations within your budget.</p> <p>The<strong> Data Analyst Training: Boost Your Career</strong> related fields are thriving across the UK, and recruiters are hiring the most knowledgeable and proficient candidates. It's a demanding field with magnitudes of lucrative choices. If you need more guidance to specialise in this area and need help knowing where to start, then <strong>StudyHub </strong>proposes a preparatory bundle. This comprehensive <strong> Data Analyst Training: Boost Your Career</strong> bundle will help you build a solid foundation to become a proficient worker in the sector.</p> <p><strong>This Data Analyst Training: Boost Your Career Bundle consists of the following</strong><strong> 30 </strong><strong>CPD Accredited Premium courses - </strong></p> <ul> <li>Course 01 :Diploma in Data Analysis Fundamentals</li><li>Course 02 :Google Data Studio: Data Analytics</li><li>Course 03 :Statistics</li><li>Course 04 :Statistical Analysis</li><li>Course 05 :Research Methods in Business</li><li>Course 06 :Business Intelligence and Data Mining</li><li>Course 07 :Quick Data Science Approach from Scratch</li><li>Course 08 :Microsoft Power BI - Master Power BI in 90 Minutes!</li><li>Course 09 :PowerBI Formulas</li><li>Course 10 :R Programming for Data Science</li><li>Course 11 :Python Data Science</li><li>Course 12 :Data Science &amp; Machine Learning with Python</li><li>Course 13 :Data Science &amp; Machine Learning with R</li><li>Course 14 :Excel Data Tools and Data Management</li><li>Course 15 :Master JavaScript with Data Visualization</li><li>Course 16 :Mastering SQL Programming</li><li>Course 17 :Fundamentals of Business Analysis</li><li>Course 18 :Financial Analysis</li><li>Course 19 :Financial Statement Analysis Masterclass</li><li>Course 20 :Financial Modeling Using Excel</li><li>Course 21 :Investment Analyst</li><li>Course 22 :Technical Analysis Masterclass for Trading &amp; Investing</li><li>Course 23 :Understanding Financial Statements and Analysis</li><li>Course 24 :Strategic Planning and Analysis for Marketing</li><li>Course 25: Stock Trading Analysis with Volume Trading</li><li>Course 26: Time Management Training - Online Course</li><li>Course 27: Complete Communication Skills Master Class for Life</li><li>Course 28: Public Speaking</li><li>Course 29: Minute Taking Executive Training</li><li>Course 30: Receptionist Skills</li></ul> <p><strong>3 </strong><strong>Extraordinary Career Oriented courses that will assist you in reimagining your thriving techniques-</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></ul> <p><strong>Learning Outcome</strong></p> <p><strong>This tailor-made </strong><strong>Data Analyst Training: Boost Your Career</strong><strong> bundle will allow you to-</strong></p> <ul> <li>Uncover your skills and aptitudes to break new ground in the related fields</li><li>Deep dive into the fundamental knowledge </li><li>Acquire some hard and soft skills in this area </li><li>Gain some transferable skills to elevate your performance</li><li>Maintain good report with your clients and staff</li><li>Gain necessary office skills and be tech savvy utilising relevant software </li><li>Keep records of your work and make a report </li><li>Know the regulations around this area</li><li>Reinforce your career with specific knowledge of this field </li><li>Know your legal and ethical responsibility as a professional in the related field</li></ul> <p>This Data Analyst Training: Boost Your Career Bundle resources were created with the help of industry experts, and all subject-related information is kept updated on a regular basis to avoid learners from falling behind on the latest developments.</p> <p><strong>Certification</strong></p> <p>After studying the complete training you will be able to take the assessment. After successfully passing the assessment you will be able to claim all courses pdf certificates and <strong>1 hardcopy certificate for the Title Course completely free</strong>. Other Hard Copy certificates need to be ordered at an additional cost of •8.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        330 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>Ambitious learners who want to strengthen their CV for their desired job should take advantage of the Data Analyst Training: Boost Your Career bundle! This bundle is also ideal for professionals looking for career advancement.</p> 
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                             <p>To participate in this course, all you need is -</p> <ul> <li>A smart device</li><li>A secure internet connection</li><li>And a keen interest in Data Analyst Training: Boost Your Career</li></ul> 
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                             <p>Upon completing this essential Bundle, you will discover a new world of endless possibilities. These courses will help you to get a cut above the rest and allow you to be more efficient in the relevant fields.</p> 
                        </div>

Career Development

Data Analyst

Data Analyst Training: Boost Your Career

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p></p><p>This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.</p><p></p>Overview<p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.</p><p></p><p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.</p><p></p>Prerequisites<p></p><li>Creating cloud resources in Microsoft Azure.</li>  <li>Using Python to explore and visualize data.</li>  <li>Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.</li>  <li>Working with containers</li>  <li>AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience.</li><p></p></div><div id="course-pills-2"><h3>1 - Design a data ingestion strategy for machine learning projects</h3> <ul> <li>Identify your data source and format</li> <li>Choose how to serve data to machine learning workflows</li> <li>Design a data ingestion solution</li> </ul> <h3>2 - Design a machine learning model training solution</h3> <ul> <li>Identify machine learning tasks</li> <li>Choose a service to train a machine learning model</li> <li>Decide between compute options</li> </ul> <h3>3 - Design a model deployment solution</h3> <ul> <li>Understand how model will be consumed</li> <li>Decide on real-time or batch deployment</li> </ul> <h3>4 - Design a machine learning operations solution</h3> <ul> <li>Explore an MLOps architecture</li> <li>Design for monitoring</li> <li>Design for retraining</li> </ul> <h3>5 - Explore Azure Machine Learning workspace resources and assets</h3> <ul> <li>Create an Azure Machine Learning workspace</li> <li>Identify Azure Machine Learning resources</li> <li>Identify Azure Machine Learning assets</li> <li>Train models in the workspace</li> </ul> <h3>6 - Explore developer tools for workspace interaction</h3> <ul> <li>Explore the studio</li> <li>Explore the Python SDK</li> <li>Explore the CLI</li> </ul> <h3>7 - Make data available in Azure Machine Learning</h3> <ul> <li>Understand URIs</li> <li>Create a datastore</li> <li>Create a data asset</li> </ul> <h3>8 - Work with compute targets in Azure Machine Learning</h3> <ul> <li>Choose the appropriate compute target</li> <li>Create and use a compute instance</li> <li>Create and use a compute cluster</li> </ul> <h3>9 - Work with environments in Azure Machine Learning</h3> <ul> <li>Understand environments</li> <li>Explore and use curated environments</li> <li>Create and use custom environments</li> </ul> <h3>10 - Find the best classification model with Automated Machine Learning</h3> <ul> <li>Preprocess data and configure featurization</li> <li>Run an Automated Machine Learning experiment</li> <li>Evaluate and compare models</li> </ul> <h3>11 - Track model training in Jupyter notebooks with MLflow</h3> <ul> <li>Configure MLflow for model tracking in notebooks</li> <li>Train and track models in notebooks</li> </ul> <h3>12 - Run a training script as a command job in Azure Machine Learning</h3> <ul> <li>Convert a notebook to a script</li> <li>Run a script as a command job</li> <li>Use parameters in a command job</li> </ul> <h3>13 - Track model training with MLflow in jobs</h3> <ul> <li>Track metrics with MLflow</li> <li>View metrics and evaluate models</li> </ul> <h3>14 - Perform hyperparameter tuning with Azure Machine Learning</h3> <ul> <li>Define a search space</li> <li>Configure a sampling method</li> <li>Configure early termination</li> <li>Use a sweep job for hyperparameter tuning</li> </ul> <h3>15 - Run pipelines in Azure Machine Learning</h3> <ul> <li>Create components</li> <li>Create a pipeline</li> <li>Run a pipeline job</li> </ul> <h3>16 - Register an MLflow model in Azure Machine Learning</h3> <ul> <li>Log models with MLflow</li> <li>Understand the MLflow model format</li> <li>Register an MLflow model</li> </ul> <h3>17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning</h3> <ul> <li>Understand Responsible AI</li> <li>Create the Responsible AI dashboard</li> <li>Evaluate the Responsible AI dashboard</li> </ul> <h3>18 - Deploy a model to a managed online endpoint</h3> <ul> <li>Explore managed online endpoints</li> <li>Deploy your MLflow model to a managed online endpoint</li> <li>Deploy a model to a managed online endpoint</li> <li>Test managed online endpoints</li> </ul> <h3>19 - Deploy a model to a batch endpoint</h3> <ul> <li>Understand and create batch endpoints</li> <li>Deploy your MLflow model to a batch endpoint</li> <li>Deploy a custom model to a batch endpoint</li> <li>Invoke and troubleshoot batch endpoints</li> </ul></div>

Nexus Human

Data Engineering

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

Azure Machine Learning

DP-100T01 Designing and Implementing a Data Science Solution on Azure

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 (ML)

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>

TensorFlow

Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning &amp; More!

The Complete Machine Learning Course with Python

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					<div><p>The comprehensive Machine Learning - Use in Flutter has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Machine Learning - Use in Flutter today, and learn from the very best the industry has to offer!</p></div>
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					<div><p>This best selling Machine Learning - Use in Flutter has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Machine Learning - Use in Flutter is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p><p>The Machine Learning - Use in Flutter is CPD-accredited, so you can be confident you're completing a quality training course which will boost your CV and enhance your career potential. The Machine Learning - Use in Flutter 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 Machine Learning - Use in Flutter, 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 Machine Learning - Use in Flutter 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 Machine Learning - Use in Flutter 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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Learning & Development

Learning To Learn

Machine Learning - Use in Flutter

<strong>This course will take you through the fundamental concepts of machine learning (ML) and artificial intelligence (AI). By the end of this course, you will be ready to dive into the advanced concepts of ML.</strong>
        <p>Instead of using hard-coded rules for performing something, artificial intelligence (AI) and machine learning (ML) prepare the machines to learn things from data to decipher the complex patterns automatically and then use it for building multiple use cases. If you too want to make applications and solve complex problems using AI and ML, then this course will help you to get started with the basics.

The course starts by highlighting the learning objectives and explains the rise of AI in today's world. Next, you will be introduced to the concepts of ML. You will learn to understand ML terminologies and learn how to train a model. Towards the end, you will become familiar with the classification of ML systems, including the topics of supervised and unsupervised learning, regression, clustering, and reinforcement.

By the end of this course, you will have a fundamental knowledge of AI and ML.

All the resource for this course are available at https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginners---Level-1</p>
        <h2>What You Will Learn</h2><p>Find out why machine learning (ML) is called a black box<br>Get to grips with the features and labels of ML<br>Uncover techniques for training ML models<br>Find out the differences between supervised and unsupervised learning<br>Understand regression, clustering, and dimension reduction</p>
        <h2>Audience</h2><p>If you are a developer, product or project manager, engineer, or a data science enthusiast, who is looking to learn the fundamentals of artificial intelligence (AI) and machine learning (ML), this course is for you. There is no prerequisite to start this course as it is specially designed for absolute beginners.</p>
        <h2>Approach</h2><p>With the help of simple narration, interesting examples, and practical tips, this course helps you to get started with artificial intelligence (AI) and machine learning (ML).</p>
        <h2>Key Features</h2><p>Learn the basics of artificial intelligence (AI), machine learning (ML), and deep learning * Find out how ML helps in training a model * Discover how ML systems are classified</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginners---Level-1</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 1!</h4><p></p><br><h4>2. The Rise of Artificial Intelligence</h4><p></p><br><h4>3. Introduction to Machine Learning</h4><p></p><br><h4>4. Classification of ML Systems</h4><p></p><br><h4>5. Course Summary</h4><p></p>

Deep Learning

This course will take you through the fundamental concepts of machine learning (ML) and artificial intelligence (AI). By the end of this course, you will be ready to dive into the advanced concepts of ML.

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