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<strong>This comprehensive course will help you learn the basics to advanced mechanisms of chatbot development using deep learning with Python. This course is a complete package for beginners to learn chatbot fundamentals with deep learning and its applications and build it from scratch using deep learning (RNNs) with Python.</strong>
        <p>AI-powered chatbots are also capable of automating various tasks, including sales and marketing, customer service, and administrative and operational tasks. In this course about developing advanced chatbots with deep learning, we will understand their applications and build from scratch using deep learning with Python.

The course begins with a brief overview and the fundamentals of deep learning for chatbots. We will understand and compare conventional chatbots with deep learning-based chatbots. Then, we will explore self-learning chatbots, including generative chatbots and retrieval chatbots. You will learn more about deep learning-empowered chatbot features and compare and distinguish the abilities of conventional chatbots and self-learning chatbots in real action. We will focus on chatbot development with deep learning, tokenization, setting up an Encoder-Decoder, implementing RNN-based model development, and finally, training, testing, and validating the chatbot we developed.

Upon completing this course successfully, you will relate concepts and understand theories of chatbots in various domains, understand and implement deep learning models for building real-world chatbots, and evaluate deep learning-based chatbot models.

All resources are available at: https://github.com/PacktPublishing/Advanced-Chatbots-with-Deep-Learning-Python</p>
        <h2>What You Will Learn</h2><p>Relate the concepts and theories for chatbots in various domains<br>Compare conventional chatbots with deep learning-based chatbots<br>Understand deep learning algorithms for chatbots<br>Implement deep learning models for building real-world chatbots<br>Learn about tokenization and setting up an encoder-decoder<br>Implement recurrent neural network-based model development</p>
        <h2>Audience</h2><p>This course is designed for individuals looking to advance their skills in applied deep learning, acquire knowledge regarding the relationships of data analysis with deep learning, wish to build customized chatbots for their applications, learn to implement deep learning algorithms for chatbots, and are passionate about rule-based and self-learning chatbots. Deep learning practitioners/scholars working on chatbot concepts would benefit from this course. No prior knowledge of chatbots, deep learning, data analysis, or mathematics is needed. Basic to intermediate Python knowledge is required.</p>
        <h2>Approach</h2><p>The course is crafted to help you understand the impact of chatbots in real-world applications and provides a unique hands-on experience using a project. This course is easily understandable, with engaging content covering necessary theoretical concepts, a practical approach with live coding, and an in-depth project covering the complete course content.</p>
        <h2>Key Features</h2><p>Learn basic to advanced mechanisms of developing chatbots using deep learning with Python * Use Python to evaluate datasets based on conversational notes, online resources, and websites * Explore conventional/self-learning chatbots in action and chatbot development with deep learning</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Advanced-Chatbots-with-Deep-Learning-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>This section focuses on introducing the author and the AI Sciences group and describes the course content you will be learning.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Course and Instructor Introduction</p><p style='margin: 0'>In this video, we will be introduced to the course's author and his qualifications and experience in teaching learners on the online platform.</p></td></tr><tr><td style='padding: 15px;'><p>2. AI Sciences Introduction</p><p style='margin: 0'>This video briefly introduces the AI Sciences group and discusses the benefits of learning through AI Sciences.</p></td></tr><tr><td style='padding: 15px;'><p>3. Course Description</p><p style='margin: 0'>In this lesson, we will get an overview of what is covered in the course, including a comparison of chatbots and the benefits of chatbots. We will look at the chatbots in action. We will also look at deep learning frameworks in chatbots.</p></td></tr></tbody></table><br><h4>2. Fundamentals of Chatbots for Deep Learning</h4><p>This section focuses on the basics of chatbots, how deep learning benefits chatbots, conventional versus AI chatbots, the use of chatbots in the medical field, and the use of chatbots in business and ecommerce.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Module Introduction</p><p style='margin: 0'>This introduction video elaborates on the concepts to be covered in this module, including comparing chatbots, the conventional versus AI chatbots, and use of chatbots in various fields of applications.</p></td></tr><tr><td style='padding: 15px;'><p>2. Conventional Versus AI Chatbots</p><p style='margin: 0'>In this video, we will understand conventional and artificial intelligence-based chatbots and understand the differences between the two kinds.</p></td></tr><tr><td style='padding: 15px;'><p>3. Generative Versus Retrieval Chatbots</p><p style='margin: 0'>In this lecture, you will learn about a generative and retrieval chatbot and compare the differences between the two chatbots.</p></td></tr><tr><td style='padding: 15px;'><p>4. Benefits of Deep Learning Chatbots</p><p style='margin: 0'>In this video, we will look at what deep learning chatbots are and how they work. We will also understand the benefits of deep learning chatbots, including improved customer experience, service integration, customer care, personalized services, and saving resources.</p></td></tr><tr><td style='padding: 15px;'><p>5. Chatbots in Medical Domain</p><p style='margin: 0'>We will explore the first kind of chatbot operating in the medical domain. We will look at the benefits, including the ability to schedule appointments, check patient symptoms, provide support, help with coverage and insurance claims, and improve the patient experience.</p></td></tr><tr><td style='padding: 15px;'><p>6. Chatbots in Business</p><p style='margin: 0'>In this video, we will understand the benefits of chatbots in businesses, including lead qualification, lead nurturing, and data mining techniques.</p></td></tr><tr><td style='padding: 15px;'><p>7. Chatbots in Ecommerce</p><p style='margin: 0'>Let's understand the benefits of chatbots in ecommerce, including personalized services, real-time interaction, collection of feedback, provide metrics, lead generation, deep analytics, and storytelling.</p></td></tr></tbody></table><br><h4>3. Deep Learning-Based Chatbot Architecture and Development</h4><p>This section focuses on chatbot architecture and development based on deep learning, including understanding deep learning architecture, encoders and decoders, data preparation, importing libraries, and making predictions.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Module Introduction</p><p style='margin: 0'>In this video, you will learn more about deep learning and the general architecture, chatbot development with deep learning, and its related concepts.</p></td></tr><tr><td style='padding: 15px;'><p>2. Deep Learning Architecture</p><p style='margin: 0'>This video elaborates on the deep learning architecture in chatbots, integration of deep learning with chatbots, natural language processing (NLP), source content, interaction history, and analytics.</p></td></tr><tr><td style='padding: 15px;'><p>3. Encoder Decoder</p><p style='margin: 0'>In this video, we will understand what encoder and decoder are, their architecture, and long short-term memory (LSTM), a neural network used in deep learning.</p></td></tr><tr><td style='padding: 15px;'><p>4. Steps Involved</p><p style='margin: 0'>In this lesson, you will learn about the various steps involved in developing chatbots based on deep learning techniques. We will install the required packages, define chat models and tokenization, and set up the encoder-decoder model.</p></td></tr><tr><td style='padding: 15px;'><p>5. Project Overview and Packages</p><p style='margin: 0'>After theoretically learning about chatbots, we will now develop a chatbot practically by importing the requisite libraries-TensorFlow NumPy, Keras, and Pickle. We will build a chatbot based on a story and make predictions of true or false.</p></td></tr><tr><td style='padding: 15px;'><p>6. Importing Libraries</p><p style='margin: 0'>This video demonstrates how to import step by step the four main libraries required for our project, including TensorFlow, NumPy, Keras, and Pickle, and you will learn about importing Sequential and Model.</p></td></tr><tr><td style='padding: 15px;'><p>7. Data Preparation</p><p style='margin: 0'>We will use the two datasets available for our project, the training QA and the testing QA. We will save them in our project folder and invoke them as needed.</p></td></tr><tr><td style='padding: 15px;'><p>8. Develop Vocabulary</p><p style='margin: 0'>In this video, you will learn to combine the datasets, test data, and train data; we will use the all_data function to combine the datasets.</p></td></tr><tr><td style='padding: 15px;'><p>9. Max Story and Question Length</p><p style='margin: 0'>In this video, you will learn to define the project's story length and question length, determined by the number of words in the story or question.</p></td></tr><tr><td style='padding: 15px;'><p>10. Tokenizer</p><p style='margin: 0'>You will learn to import the tokenizer with and without filters. We will fit the tokenizer into our vocabulary using the fit_on_texts built-in command.</p></td></tr><tr><td style='padding: 15px;'><p>11. Separation and Sequence</p><p style='margin: 0'>In this video, you will learn to make the train-test story questions and answers. We will then use a for loop to enter the story, question, and answer into the respective parts.</p></td></tr><tr><td style='padding: 15px;'><p>12. Vectorize Stories</p><p style='margin: 0'>In this video, we will understand how to vectorize the story by defining functions, using the data, and developing an index and tokenizer. We will also determine the maximum story length calculated.</p></td></tr><tr><td style='padding: 15px;'><p>13. Vectorizing Train and Test Data</p><p style='margin: 0'>After creating the vectorization function, we will input the stories, queries, and answers using the vectorize function that we created using the train data.</p></td></tr><tr><td style='padding: 15px;'><p>14. Encoding</p><p style='margin: 0'>We will begin to develop our deep learning model and input placeholders to store the maximum story length, question length, and define the vocabulary size. We will now build our encoder using the sequential model.</p></td></tr><tr><td style='padding: 15px;'><p>15. Answer and Response</p><p style='margin: 0'>After learning to create our encoders for the input sequences and the questions, the encoders will match the data and obtain the responses.</p></td></tr><tr><td style='padding: 15px;'><p>16. Model Completion</p><p style='margin: 0'>In this video, after training and testing the data, querying the questions, and obtaining responses, we are now at model completion with compiling the questions and responses to check for accuracy.</p></td></tr><tr><td style='padding: 15px;'><p>17. Predictions</p><p style='margin: 0'>After checking our model for accuracy, we will make predictions of our results from the model we created. We will visualize the predictions using the test data.</p></td></tr></tbody></table>

Packt

Web Development

Python

This comprehensive course will help you learn the basics to advanced mechanisms of chatbot development using deep learning with Python. This course is a complete package for beginners to learn chatbot fundamentals with deep learning and its applications and build it from scratch using deep learning (RNNs) with Python.

Advanced Chatbots with Deep Learning and Python

General Admission

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					<div><p>Deep learning is one of the most powerful machine learning techniques, and R is a popular programming language for data science. This 'Deep Learning Neural Network with R' course will teach you how to build and train deep learning models in R using real-world projects.</p><p>You'll start by learning the basics of neural networks, including single-layer and multi-layer networks. Using the Keras library, you'll then learn how to implement these networks in R.</p><p>Once you understand the basics well, you'll embark on two hands-on projects. In the first project, you'll build a single-layer neural network to predict crop yields in agriculture. In the second project, you'll build a multi-layer neural network to predict war deaths.</p><p>As you progress, the curriculum seamlessly transitions you into the realm of multi-layer neural networks, tackling the complexities of war-related death data. This step-up solidifies your grasp of neural networks and enhances your ability to handle intricate datasets, extract meaningful information, and craft informed predictions. The projects are designed to simulate world scenarios, ensuring you are well-prepared to apply your newfound knowledge to valuable applications.</p><p>By the end of this 'Deep Learning Neural Network with R' course, you will have mastered the art and science of neural networks, armed with the confidence and skills to analyze diverse datasets and make predictions that can drive decisions. The knowledge and valuable skills you gain will add value to your professional repertoire and open doors to numerous opportunities in the fast-evolving world of data analysis. This is your opportunity to step into the future and make a mark in the world of deep learning neural networks.</p></div>
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										<span>Master single-layer neural networks and their application in agriculture.</span>
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										<span>Navigate multi-layer neural networks for complex data analysis.</span>
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										<span>Enhance your data analysis portfolio with practical projects.</span>
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			<h2> <b>Requirements</b></h2>		</div>
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                                <h2>Course Curriculum</h2>
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					<td colspan="4"><strong>Section 01: Single Layer Neural Networks Project - Agriculture (Part - 1)</strong></td>
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					<td>Reviewing Dataset</td><td><span>🕐 00:14:00</span></td>
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					<td>Creating Dataframes</td><td><span>🕐 00:09:00</span></td>
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					<td>Generating Output</td><td><span>🕐 00:12:00</span></td>
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					<td colspan="4"><strong>Section 02: Single Layer Neural Networks Project - Agriculture (Part - 2)</strong></td>
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					<td>Running Neural Network Code</td><td><span>🕐 00:11:00</span></td>
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					<td>Importing Dataset</td><td><span>🕐 00:09:00</span></td>
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					<td>Neural Network Plots for Hidden Layer 1</td><td><span>🕐 00:08:00</span></td>
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					<td colspan="4"><strong>Section 03: Multi-Layer Neural Networks Project - Deaths in wars (Part - 1)</strong></td>
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					<td>Syntax and Commands for MLP</td><td><span>🕐 00:11:00</span></td>
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					<td>Running the Code</td><td><span>🕐 00:08:00</span></td>
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					<td>Testing for Dataframes</td><td><span>🕐 00:13:00</span></td>
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					<td>Predict Results</td><td><span>🕐 00:08:00</span></td>
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					<td colspan="4"><strong>Section 04: Multi-Layer Neural Networks Project - Deaths in wars (Part - 2)</strong></td>
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					<td>Creating R Folder</td><td><span>🕐 00:14:00</span></td>
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					<td>Generating Output Plot</td><td><span>🕐 00:12:00</span></td>
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					<td>Testing and Predicting the Outputs</td><td><span>🕐 00:16:00</span></td>
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Skill Up

Unleash the power of deep learning neural networks with R! Learn to build and train models to solve real problems in agriculture, war deaths, and more.

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Data Analyst

Data Analyst (Data Analytics) - CPD Certified

<p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">✿ 17</strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&nbsp;in 1 "Geographic Information System (GIS) Diploma" Bundle ✿</strong></p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This Geographic Information System (GIS) Diploma training offers :</strong></p><ul style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">17&nbsp;</strong>Free PDF Certificates</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">1</strong>&nbsp;Hard Copy Certificate</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Free&nbsp;</strong>Assessment</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Lifetime&nbsp;</strong>Access</li></ul><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Geographic Information System (GIS)&nbsp;</strong>is a rapidly growing field, with a predicted&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">growth&nbsp;</strong>rate of&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">10%</strong>&nbsp;over the next five years. 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So, if you are willing to start your journey in this rapidly growing sector, our Geographic Information System (GIS) Diploma will cover everything you need to know to get started.</p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">The&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Geographic Information System (GIS)&nbsp;</strong>diploma provides a comprehensive introduction to one of the most critical tools in geographic data analysis and spatial information management.</p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">Throughout the&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Geographic Information System (GIS)&nbsp;</strong>diploma, students will delve into various techniques and methodologies used to capture, store, manipulate, analyse, manage, and present spatial or geographic data. The curriculum is designed to provide a balanced mix of theoretical knowledge and applications, empowering students to effectively utilise GIS software and tools. By the end of the Geographic Information System (GIS) bundle, learners will have developed the competency to apply Geographic Information System (GIS) technology in various fields, including urban planning, environmental management, and resource allocation.</p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">The&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Geographic Information System (GIS)&nbsp;</strong>diploma is tailored to cater to a diverse audience, from beginners to those with some prior knowledge of the subject. It addresses the growing demand for GIS professionals who can handle complex spatial data and provide insightful solutions to real-world problems.</p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">By enrolling in this&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Geographic Information System (GIS)</strong>&nbsp;bundle, students will not only enhance their understanding of Geographic Information System (GIS) but also open up new career opportunities in an ever-evolving technological landscape.</p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This Geographic Information System (GIS) Diploma Bundle Consists the Following Courses:</strong></p><ol style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><li fr-original-style="" style="box-sizing: border-box;">ArcGIS for Spatial Analysis</li><li fr-original-style="" style="box-sizing: border-box;">ArcGIS for Remote Sensing</li><li fr-original-style="" style="box-sizing: border-box;">Create Smart Maps in Python and Leaflet Level 3</li><li fr-original-style="" style="box-sizing: border-box;">Machine Learning for Predictive Maps in Python and Leaflet</li><li fr-original-style="" style="box-sizing: border-box;">Web Scraping and Mapping Dam Levels in Python and Leaflet Level 4</li><li fr-original-style="" style="box-sizing: border-box;">Maps in R Shiny and Leaflet</li><li fr-original-style="" style="box-sizing: border-box;">The Basics of ArcGIS for Hydrology</li><li fr-original-style="" style="box-sizing: border-box;">Learn to Use Python for Spatial Analysis in ArcGIS</li><li fr-original-style="" style="box-sizing: border-box;">Python Programming Complete Training</li><li fr-original-style="" style="box-sizing: border-box;">Archaeology Course</li><li fr-original-style="" style="box-sizing: border-box;">Geology Course &ndash; Online &amp; CPD Accredited</li><li fr-original-style="" style="box-sizing: border-box;">CompTIA Network+ Certification</li><li fr-original-style="" style="box-sizing: border-box;">Learn Secure Programming for Web Applications</li><li fr-original-style="" style="box-sizing: border-box;">Ethical Hacking Masterclass</li><li fr-original-style="" style="box-sizing: border-box;">Microsoft SQL Queries</li><li fr-original-style="" style="box-sizing: border-box;">Project Management Complete Training</li><li fr-original-style="" style="box-sizing: border-box;">Critical Thinking &amp; Problem Solving</li></ol><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">Enrol now for a successful GIS career!</p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Learning Outcome of this Geographic Information System (GIS) Diploma:</strong></p><ul style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><li fr-original-style="" style="box-sizing: border-box;">Understand the fundamental concepts and principles of Geographic Information System (GIS).</li><li fr-original-style="" style="box-sizing: border-box;">Apply Geographic Information System (GIS) techniques to analyse spatial data.</li><li fr-original-style="" style="box-sizing: border-box;">Utilise GIS software for mapping and data visualisation.</li><li fr-original-style="" style="box-sizing: border-box;">Create Smart Maps in Python and Leaflet.</li><li fr-original-style="" style="box-sizing: border-box;">Learn Python and Leaflet for Machine Learning for Predictive Maps.</li><li fr-original-style="" style="box-sizing: border-box;">Know Web Scraping and Dam Level Mapping.</li><li fr-original-style="" style="box-sizing: border-box;">Study programming in Python.</li><li fr-original-style="" style="box-sizing: border-box;">Acquire knowledge of secure programming for web applications.</li><li fr-original-style="" style="box-sizing: border-box;">Learn about project management, Microsoft SQL, and ethical hacking.</li></ul><h2 fr-original-style=" color: rgb(15, 21, 26);" style="color: rgb(15, 21, 26); box-sizing: border-box;" id="isPasted">Certificates</h2><div fr-original-style=" color: rgb(15, 21, 26);" style="color: rgb(15, 21, 26); box-sizing: border-box;"><p fr-original-style=" color: var(--text);" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Digital Certificate</strong></p><p fr-original-style=" color: var(--text);" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This bundle comes with a free&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">CPD Accredited PDF Copy certificate+ Transcript&nbsp;</strong>(according to the Learner&#39;s Choice). For additional courses, it costs&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&pound;14.99</strong>&nbsp;per copy.</p><p fr-original-style=" color: var(--text);" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Hard Copy Certificate</strong></p><p fr-original-style=" color: var(--text);" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Get&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">CPD Accredited Hard Copy certificate</strong>&nbsp;for&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&pound;19.99</strong>&nbsp;per copy. The delivery fee for the Hard Copy certificate, however, is free for UK residents, whereas it costs&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">&pound;10</strong>&nbsp;for international students as delivery charge.</p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Here is the course curriculum for the primary Title Course in this bundle:</strong></p><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">ArcGIS for Spatial Analysis</strong></p><ul style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><li fr-original-style="" style="box-sizing: border-box;">Module 01: Point Density Analysis</li><li fr-original-style="" style="box-sizing: border-box;">Module 02: Raster Calculator and Vector Isolation</li><li fr-original-style="" style="box-sizing: border-box;">Module 03: Raster to Topography</li><li fr-original-style="" style="box-sizing: border-box;">Module 04: Raster Reclassification</li><li fr-original-style="" style="box-sizing: border-box;">Module 05: Raster Overlay</li><li fr-original-style="" style="box-sizing: border-box;">Module 06: Slope Analysis and Hydrology tools</li><li fr-original-style="" style="box-sizing: border-box;">Module 07: Introduction to TIFF Files</li><li fr-original-style="" style="box-sizing: border-box;">Module 08: Introduction to 3D Surfaces</li><li fr-original-style="" style="box-sizing: border-box;">Module 09: Satellite Images and TIN Surfaces</li><li fr-original-style="" style="box-sizing: border-box;">Module 10: Exercise</li></ul><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">----------and 16 more Courses----------</strong></p><section style="color: rgb(15, 21, 26); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(15, 21, 26);"><h2 style="color: var(--bs-heading-color); box-sizing: border-box;" fr-original-style=" color: var(--bs-heading-color);">Who is this course for?</h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Geographic Information System (GIS)&nbsp;</strong>training is open to everyone. Specially for-</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Individuals interested in geographic data analysis</li><li fr-original-style="" style="box-sizing: border-box;">Urban planners and environmental managers</li><li fr-original-style="" style="box-sizing: border-box;">Professionals in logistics and transportation</li><li fr-original-style="" style="box-sizing: border-box;">Students pursuing geography or related fields</li><li fr-original-style="" style="box-sizing: border-box;">Data analysts seeking to specialise in GIS</li></ul></section><section style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><h2 style="color: var(--bs-heading-color); box-sizing: border-box;" fr-original-style=" color: var(--bs-heading-color);">Requirements</h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">For this&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Geographic Information System (GIS)</strong>&nbsp;bundle, you don&#39;t need any formal qualifications.</p></section><section style="color: rgb(15, 21, 26); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);"><h2 style="color: var(--bs-heading-color); box-sizing: border-box;" fr-original-style=" color: var(--bs-heading-color);">Career path</h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Unlock diverse career opportunities with our&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Geographic Information System (GIS)</strong>&nbsp;bundle. Explore these lucrative paths:</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">GIS Analyst: &pound;25,000 - &pound;35,000</li><li fr-original-style="" style="box-sizing: border-box;">Urban Planner: &pound;30,000 - &pound;45,000</li><li fr-original-style="" style="box-sizing: border-box;">Environmental Consultant: &pound;28,000 - &pound;40,000</li><li fr-original-style="" style="box-sizing: border-box;">Cartographer: &pound;22,000 - &pound;35,000</li><li fr-original-style="" style="box-sizing: border-box;">Geospatial Data Scientist: &pound;40,000 - &pound;60,000</li><li fr-original-style="" style="box-sizing: border-box;">Remote Sensing Analyst: &pound;30,000 - &pound;50,000</li></ul></section></div>

Best Saving Deal | 17-in-1 Premium Bundle | 170 CPD Points | Free PDF & transcript Certificates | Lifetime Access


Geographic Information System (GIS) Diploma - CPD Accredited


<p><strong>***24 Hour Limited Time Flash Sale***<br /><br /></strong><strong> IT Support Technical Skills Bootcamp Admission Gifts <br /><br /></strong><strong> FREE PDF &amp; Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter</strong></p><p>As digital transformation accelerates, demand for qualified IT support technicians surges in the UK. The IT industry is booming, with an expected growth of <strong>12% by 2027</strong>, creating over<strong> 1 million</strong> new jobs. Do you have an interest in maintaining networks, securing systems, and providing technical support? This IT Support Technical Skills Bootcamp bundle delivers the well-rounded expertise today's IT teams need.</p><p>Designed to cater to the needs of both seasoned professionals and aspiring newcomers, our IT Support Technical Skills Bootcamp bundle is a comprehensive programme 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 IT Support Technical Skills Bootcamp 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 IT Support Technical Skills Bootcamp Career Bundle:</strong></p><ul><li><strong>Course 01: </strong>Advanced Diploma in IT Support Technician at QLS Level 7</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>ASP.Net MVC and Entity Framework Course</li><li><strong>Course 08: </strong>Computer Operating System and Troubleshooting</li><li><strong>Course 09: </strong>PLC Programming Diploma</li><li><strong>Course 10: </strong>Learn Spring &amp; Angular Material with a Full Web Application</li><li><strong>Course 11: </strong>SQL Server 101: Microsoft SQL Server for Absolute Beginners</li><li><strong>Course 12: </strong>JavaScript</li><li><strong>Course 13: </strong>Python Course</li><li><strong>Course 14: </strong>Learn Ethical Hacking with Kali Linux</li><li><strong>Course 15: </strong>Building Your Own Computer Course</li><li><strong>Course 16: </strong>Ruby on Rails Web Application Framework</li><li><strong>Course 17: </strong>Create Your First Responsive Website</li><li><strong>Course 18: </strong>Data Science and Visualisation with Machine Learning</li><li><strong>Course 19: </strong>Cisco ASA Firewall Training Course</li><li><strong>Course 20: </strong>SQL For Data Analytics &amp; Database Development</li><li><strong>Course 21: </strong>TypescriptU&amp;P AI - Natural Language Processing (NLP) with Python</li><li><strong>Course 22:</strong>C# (C-Sharp)</li><li><strong>Course 23:</strong>MS Word Essentials - The Complete Word Course - Level 3</li><li><strong>Course 24: </strong>Web Design (HTML, CSS, Bootstrap) Complete Course</li><li><strong>Course 25: </strong>Website Hacking From Scratch</li><li><strong>Course 26: </strong>Diploma in Front-End Web Development (HTML, CSS, &amp; Bootstrap)</li><li><strong>Course 27: </strong>Data Protection (GDPR) Practitioner</li><li><strong>Course 28: </strong>SQL Database Administrator</li><li><strong>Course 29: </strong>Cisco ASA Firewall Training Course</li><li><strong>Course 30: </strong>IT: Ethical Hacking &amp; IT Security</li></ul><p>With IT Support Technical Skills Bootcamp, 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.</p><p><strong>Learning Outcomes of IT Support Technical Skills</strong></p><ul><li>Diagnose and troubleshoot IT hardware and software issues.</li><li>Implement network security best practices and manage risks.</li><li>Gain industry-recognized CompTIA certifications.</li><li>Develop web applications using popular frameworks and languages.</li><li>Automate tasks with scripting and programming skills.</li><li>Build a strong foundation for further specialization in IT.</li></ul><p>Enrol in IT Support Technical Skills Bootcamp today and take the first step towards achieving your goals and dreams.</p><p><strong>Why buy this IT Support Technical Skills Bootcamp?</strong></p><ul><li>Get a Free CPD Accredited Certificate upon completion of the course</li><li>Get a free student ID card with this training program</li><li>The course is affordable and simple to understand</li><li>This course is entirely online, interactive lesson with voiceover audio</li><li>Lifetime access to the course materials</li><li>The training program comes with 24/7 tutor support</li></ul> <p><strong>Start your learning journey straightaway with our IT Support Technical Skills Bootcamp Training!</strong></p><p>IT Support Technical Skills Bootcamp 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 IT Support Technical Skills Bootcamp 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 IT Support Technical Skills Bootcamp course. After passing the course 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>
                                        480 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 Support Technical Skills Bootcamp course is ideal for:</p><ul><li>Students seeking mastery in IT Support Technical Skills Bootcamp</li><li>Professionals seeking to enhance IT Support Technical Skills Bootcamp skills</li><li>Individuals looking for an IT Support Technical Skills Bootcamp-related career.</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This IT Support Technical Skills Bootcamp doesn't require prior experience and is suitable for diverse learners.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This IT Support Technical Skills Bootcamp bundle will allow you to kickstart or take your career in the related sector to the next stage.</p><ul><li>IT Support Specialist</li><li>Network Administrator</li><li>Cloud Engineer</li><li>Web Developer</li><li>Security Analyst</li></ul>
                        </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

IT Support

IT Certifications

IT Skills

Computer Skills

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ICDL (International Certification of Digital Literacy)

IT Support Technical Skills Bootcamp- CPD Certified

<p><strong>***24 Hour Limited Time Flash Sale***<br /><br /></strong><strong> Learn C++ Admission Gifts <br /><br /></strong><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 Learn C++ from Scratch: The Complete Coding Guide 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 Learn C++ from Scratch: The Complete Coding Guide 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 Learn C++ from Scratch: The Complete Coding Guide 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 Learn C++ from Scratch: The Complete Coding Guide Career Bundle:</strong></p><ul><li><strong>Course 01: </strong>C++ Development: The Complete Coding Guide</li><li><strong>Course 02: </strong>Basic C# Coding</li><li><strong>Course 03: </strong>Computer Vision: C++ and OpenCV with GPU support</li><li><strong>Course 04: </strong>Python Basic Programming for Absolute Beginners</li><li><strong>Course 05: </strong>Python Programming for Everybody</li><li><strong>Course 06: </strong>Intermediate Python Coding</li><li><strong>Course 07: </strong>Higher Order Functions in Python - Level 03</li><li><strong>Course 08: </strong>Javascript Programming for Beginners</li><li><strong>Course 09: </strong>JavaScript Masterclass: ES6 Modern Development</li><li><strong>Course 10: </strong>JavaScript Foundations for Everyone</li><li><strong>Course 11: </strong>Basic Asynchronous JavaScript</li><li><strong>Course 12: </strong>SQL NoSQL Big Data and Hadoop</li><li><strong>Course 13: </strong>Level-3 Machine Learning Course with Python</li><li><strong>Course 14: </strong>Data Analytics with Tableau</li><li><strong>Course 15: </strong>R Programming for Data Science</li><li><strong>Course 16: </strong>JavaScript Functions</li><li><strong>Course 17: </strong>Introduction to Data Analysis</li><li><strong>Course 18: </strong>SQL Programming Masterclass</li><li><strong>Course 19: </strong>Complete Google Analytics Course</li><li><strong>Course 20: </strong>JavaScript Promises</li><li><strong>Course 21: </strong>jQuery Masterclass Course: JavaScript and AJAX Coding Bible</li><li><strong>Course 22: </strong>Quick Data Science Approach from Scratch</li><li><strong>Course 23: </strong>Microsoft SQL Server Development for Everyone</li><li><strong>Course 24: </strong>Learn to Use Python for Spatial Analysis in ArcGIS</li><li><strong>Course 25: </strong>Data Science with Python</li><li><strong>Course 26: </strong>C++ Coding Masterclass</li><li><strong>Course 27: </strong>C++ Programming for Absolute Beginners</li><li><strong>Course 28: </strong>Game Development using Cocos2d-x v3 C++</li><li><strong>Course 29: </strong>Tic-Tac-Toe Clone - The Complete SFML C++ Game Course</li><li><strong>Course 30: </strong>Computer Vision by Using C++ and OpenCV</li></ul><p>With Learn C++ from Scratch: The Complete Coding Guide, 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 Learn C++ from Scratch: The Complete Coding Guide today and take the first step towards achieving your goals and dreams.</p><p><strong>Why buy this Learn C++ from Scratch: The Complete Coding Guide?</strong></p><ul><li><strong>Free CPD Accredited Certificate</strong> upon completion of Learn C++ from Scratch: The Complete Coding Guide</li><li>Get <strong>a free student ID card</strong> with Learn C++ from Scratch: The Complete Coding Guide</li><li><strong>Lifetime access</strong> to the Learn C++ from Scratch: The Complete Coding Guide course materials</li><li>Get instant access to this Learn C++ from Scratch: The Complete Coding Guide course</li><li>Learn Learn C++ from Scratch: The Complete Coding Guide from anywhere in the world</li><li>24/7 tutor support with the Learn C++ from Scratch: The Complete Coding Guide course.</li></ul> <p><strong>Start your learning journey straightaway!</strong></p><p>Learn C++ from Scratch: The Complete Coding Guide 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 Learn C++ from Scratch: The Complete Coding Guide 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 Learn C++ from Scratch: The Complete Coding Guide course. After passing the Learn C++ from Scratch: The Complete Coding Guide 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>This bundle is ideal for:</p><ul><li>Students seeking mastery in this field</li><li>Professionals seeking to enhance their skills</li><li>Anyone who is passionate about this topic</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This <strong>Learn C++ from Scratch: The Complete Coding Guide</strong> doesn't require prior experience and is suitable for diverse learners.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This <strong>Learn C++ from Scratch: The Complete Coding Guide</strong> bundle will allow you to kickstart or take your career in the related sector to the next stage.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited Digital certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Hard copy certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p>If you are an <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>

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Certificate in Teaching Program (CTP)

Learn C++ from Scratch: The Complete Coding Guide - CPD Certified

<p><strong>***24 Hour Limited Time Flash Sale***<br /><br /></strong><strong> Software and Web Development Admission Gifts <br /><br /></strong><strong> FREE PDF &amp; Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter</strong></p><p>How about launching your software engineering or web development career through comprehensive training across today's most in-demand programming languages? As technology reshapes industries across the UK, skilled coders are in short supply, with over <strong>300,000 developer roles needed by 2025. </strong>This Software and Web Development bundle equips you with the skills to join this exciting field, whether you're a complete beginner or looking to upskill.</p><p>Designed to cater to the needs of both seasoned professionals and aspiring newcomers, our Software and Web Development bundle is a comprehensive program that will equip you with the essential skills and knowledge you need to succeed. Whether you're looking to advance in your current role or embark on a new career journey, this bundle has everything you need to take your professional life to the next level.</p><p><strong>But that's not all. When you enrol in Software and Web Development Online Training, you'll receive 30 CPD-Accredited PDF Certificates, Hard Copy Certificates, and our exclusive student ID card, all absolutely free.</strong></p><p><strong>Courses Are Included In this Software and Web Development Career Bundle:</strong></p><ul><li><strong>Course 01: </strong>C++ Development: The Complete Coding Guide</li><li><strong>Course 02: </strong>Basic C# Coding</li><li><strong>Course 03: </strong>Computer Vision: C++ and OpenCV with GPU support</li><li><strong>Course 04: </strong>Python Basic Programming for Absolute Beginners</li><li><strong>Course 05: </strong>Python Programming for Everybody</li><li><strong>Course 06: </strong>Data Science with Python</li><li><strong>Course 07: </strong>Need Another ONE COURSE</li><li><strong>Course 08: </strong>Basic Asynchronous JavaScript</li><li><strong>Course 09: </strong>JavaScript Promises</li><li><strong>Course 10: </strong>Learn to Use Python for Spatial Analysis in ArcGIS</li><li><strong>Course 11: </strong>Higher Order Functions in Python - Level 03</li><li><strong>Course 12: </strong>Javascript Programming for Beginners</li><li><strong>Course 13: </strong>Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li><strong>Course 14: </strong>SQL Programming Masterclass</li><li><strong>Course 15: </strong>jQuery Masterclass Course: JavaScript and AJAX Coding Bible</li><li><strong>Course 16: </strong>SQL NoSQL Big Data and Hadoop</li><li><strong>Course 17: </strong>Root Cause Analysis</li><li><strong>Course 18: </strong>Business Intelligence and Data Mining Masterclass</li><li><strong>Course 19: </strong>JavaScript Foundations for Everyone</li><li><strong>Course 20: </strong>Microsoft SQL Server Development for Everyone</li><li><strong>Course 21: </strong>R Programming for Data Science</li><li><strong>Course 22: </strong>Data Analytics with Tableau</li><li><strong>Course 23: </strong>Intermediate Python Coding</li><li><strong>Course 24: </strong>Google Data Studio: Data Analytics</li><li><strong>Course 25: </strong>Introduction to Data Analysis</li><li><strong>Course 26: </strong>Level-3 Machine Learning Course with Python</li><li><strong>Course 27: </strong>Complete Google Analytics Course</li><li><strong>Course 28: </strong>JavaScript Functions</li><li><strong>Course 29: </strong>Quick Data Science Approach from Scratch</li><li><strong>Course 30: </strong>JavaScript Masterclass: ES6 Modern Development</li></ul><p>With Software and Web Development, you'll embark on an immersive learning experience that combines interactive lessons with voice-over audio, ensuring that you can learn from anywhere in the world, at your own pace.</p><p><strong>Learning Outcomes</strong></p><ul><li>Build robust applications and analyse data with confidence.</li><li>Uncover the secrets of image processing and analysis.</li><li>Craft interactive web experiences with JavaScript frameworks.</li><li>Utilise SQL and Python for data manipulation and visualisation.</li><li>Create dynamic dashboards with Excel formulas and VBA.</li><li>Understand the world of SQL, NoSQL, and Hadoop.</li></ul><p>Enrol in Software and Web Development today and take the first step towards achieving your goals and dreams.</p><p><strong>Why buy this Bundle?</strong></p><ul><li><strong>Free CPD Accredited Certificate</strong> upon completion of Software and Web Development</li><li>Get <strong>a free student ID card</strong> with Software and Web Development</li><li><strong>Lifetime access</strong> to the Software and Web Development course materials</li><li>Get instant access to this Software and Web Development course</li><li>Learn Software and Web Development from anywhere in the world</li><li>24/7 tutor support with the Software and Web Development course.</li></ul> <p><strong>Start your learning journey straightaway with our Software and Web Development Training!</strong></p><p>The software and Web Development premium bundle consists of 30 precisely chosen courses on a wide range of topics essential for anyone looking to excel in this field. Each segment of Software and Web Development is meticulously designed to maximise learning and engagement, blending interactive content and audio-visual modules for a truly immersive experience.</p><p><strong>Certification</strong></p><p>You have to complete the assignment given at the end of the Software and Web Development course. After passing the Software and Web Development exam You will be entitled to claim a PDF &amp; Hardcopy certificate accredited by CPD Quality standards completely free.</p> <h2>
        
        <div>CPD</div>
    </h2>

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

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

                        <div id="requirements">
                            <p>This Software and Web Development doesn't require prior experience and is suitable for diverse learners.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This Software and Web Development bundle will allow you to kickstart or take your career in the related sector to the next stage.</p><ul><li>Software developer</li><li>Web developer</li><li>Data scientist</li><li>Database admin</li><li>Business analyst</li></ul>
                        </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>

Learning & Development

Computing & Software Development Tools

Software Development

Continuous Professional Development (CPD)

Software and Web Development (Online) - CPD Accredited

<h2>Description</h2><p><span><strong>Professional Proofreading And Copy Editing Diploma</strong></span></p><p><span>In today's fast-paced digital age, where content gets created every second, the importance of accurate, error-free writing becomes paramount. The Professional Proofreading And Copy Editing Diploma is an online course designed to equip participants with the skills needed to ensure that every piece of writing meets high standards of clarity, coherence, and correctness.</span></p><p><span>The course begins with an introduction to the fundamentals of proofreading and editing. Participants learn the difference between these two critical processes and understand the roles they play in the production of high-quality content. The Art of Proofreading section further delves into the intricate details of spotting errors, inconsistencies, and discrepancies in written content, ensuring that the final output is polished and perfect.</span></p><p><span>On the other hand, The Science of Editing focuses on restructuring and refining content to make it more reader-friendly and engaging. Editing isn't just about correcting mistakes but also involves enhancing the flow, structure, and tone of a document.</span></p><p><span>As the world goes digital, so does the content. Proofreading and Editing Digital Content sheds light on the nuances of handling online material. From blog posts to e-books, this segment guides participants on how to maintain the integrity of digital content, ensuring it's free from errors and compelling for the readers.</span></p><p><span>Those who aspire to build a rewarding career in this domain will find the Building a Career in Proofreading and Editing section particularly beneficial. It offers insights into the professional world of proofreading and editing, providing valuable tips on networking, building a portfolio, and setting up a successful freelance business.</span></p><p><span>Mastering Proofreading Techniques and Developing Your Editing Skills are comprehensive modules that go beyond the basics. Participants are taught advanced techniques, strategies, and tools to become adept proofreaders and editors. They will learn to tackle complex documents, ensuring that the language, style, and format align perfectly with the intended message and audience.</span></p><p><span>However, not all written content is the same. Proofreading and Editing for Different Genres teaches participants the distinct approaches required for various types of writing. Whether it's fiction, academic articles, business reports, or journalistic pieces, this section provides the expertise to handle diverse genres with ease.</span></p><p><span>In the field of proofreading and editing, it's essential to be aware of the legal and ethical considerations. The module on Legal and Ethical Considerations in Proofreading and Editing ensures participants have a firm grasp on issues like copyright, plagiarism, confidentiality, and more. It's vital knowledge for anyone serious about upholding the standards and ethics of the profession.</span></p><p><span>Lastly, The Future of Proofreading and Editing looks ahead, exploring the evolving landscape of this domain. With the rise of AI and machine learning, how will the roles of proofreaders and editors change? This section provides a futuristic perspective, preparing participants for the challenges and opportunities that lie ahead.</span></p><p><span>To sum up, the Professional Proofreading And Copy Editing Diploma is a comprehensive online course designed for those keen on mastering the art and science of proofreading and editing. Whether you're a beginner or an experienced professional looking to hone your skills, this course promises to be a valuable asset in your learning journey. Equip yourself with the expertise to ensure every piece of writing shines with perfection. Enrol today and embark on a rewarding career in the world of professional proofreading and editing.</span></p><p><span><strong>What you will learn</strong></span></p><p><span><strong>1</strong>: Introduction to Proofreading and Editing </span><br />
<span><strong>2</strong>: The Art of Proofreading </span><br />
<span><strong>3</strong>: The Science of Editing </span><br />
<span><strong>4</strong>: Proofreading and Editing Digital Content </span><br />
<span><strong>5</strong>: Building a Career in Proofreading and Editing </span><br />
<span><strong>6</strong>: Mastering Proofreading Techniques </span><br />
<span><strong>7</strong>: Developing Your Editing Skills </span><br />
<span><strong>8:</strong> Proofreading and Editing for Different Genres </span><br />
<span><strong>9</strong>: Legal and Ethical Considerations in Proofreading and Editing </span><br />
<span><strong>10</strong>: The Future of Proofreading and Editing </span></p><h4>Course Outcomes</h4><p>
After completing the course, you will receive a diploma certificate and an academic transcript from Elearn college.</p><h4>Assessment</h4><p>
Each unit concludes with a multiple-choice examination. This exercise will help you recall the major aspects covered in the unit and help you ensure that you have not missed anything important in the unit. The results are readily available, which will help you see your mistakes and look at the topic once again. If the result is satisfactory, it is a green light for you to proceed to the next chapter.</p><h4>Accreditation</h4><p>
Elearn College is a registered Ed-tech company under the UK Register of Learning( Ref No:10062668). After completing a course, you will be able to download the certificate and the transcript of the course from the website. For the learners who require a hard copy of the certificate and transcript, we will post it for them for an additional charge.</p>

Elearncollege

Professional Proofreading And Copy Editing Course

<p>Feeling Stuck in Your Career? The IT Security: CompTIA network+ with SQL -(30 in 1 Bundle)  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 IT Security: CompTIA network+ with SQL  bundle provides an engaging learning experience, helping you learn skills across various disciplines.</p><p>With IT Security: CompTIA network+ with SQL -(30 in 1 Bundle)  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 IT Security: CompTIA network+ with SQL  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 IT Security: CompTIA network+ with SQL -(30 in 1 Bundle)  bundle on your job life and career growth!</p><p><strong>This IT Security: CompTIA network+ with SQL -(30 in 1 Bundle) Comprises the Following CPD Accredited Courses:</strong></p><ul><li><strong>Course 01</strong>: IT Administration and Networking</li><li><strong>Course 02</strong>: Start an IT Asset Department</li><li><strong>Course 03</strong>: IT Helpdesk Administrator Training</li><li><strong>Course 04</strong>: CompTIA IT Fundamentals ITF+ (FCO-U61)</li><li><strong>Course 05</strong>: CompTIA Network+ Certification (N10-007)</li><li><strong>Course 06</strong>: Information Management</li><li><strong>Course 07</strong>: IT For Recruiters</li><li><strong>Course 08</strong>: The Complete Front-End Web Development Course!</li><li><strong>Course 09</strong>: Data Science &amp; Machine Learning with R from A-Z</li><li><strong>Course 10</strong>: SQL for Data Science, Data Analytics and Data Visualization</li><li><strong>Course 11</strong>: Masterclass Bootstrap 5 Course - Responsive Web Design</li><li><strong>Course 12</strong>: Web Application Penetration Testing Course</li><li><strong>Course 13</strong>: Cloud Computing / CompTIA Cloud+ (CV0-002)</li><li><strong>Course 14</strong>: CompTIA PenTest+ (Ethical Hacking)</li><li><strong>Course 15</strong>: Computer Networks Security from Scratch to Advanced</li><li><strong>Course 16</strong>: Learn Ethical Hacking From A-Z: Beginner To Expert</li><li><strong>Course 17</strong>: SQL Database Basics for Everyone</li><li><strong>Course 18</strong>: GDPR</li><li><strong>Course 19</strong>: Cyber Security Incident Handling and Incident Response</li><li><strong>Course 20</strong>: Digital Product Management</li><li><strong>Course 21</strong>: Career Development Plan Fundamentals</li><li><strong>Course 22</strong>: CV Writing and Job Searching</li><li><strong>Course 23</strong>: Learn to Level Up Your Leadership</li><li><strong>Course 24</strong>: Networking Skills for Personal Success</li><li><strong>Course 25</strong>: Ace Your Presentations: Public Speaking Masterclass</li><li><strong>Course 26</strong>: Learn to Make a Fresh Start in Your Life</li><li><strong>Course 27</strong>: Motivation - Motivating Yourself &amp; Others</li><li><strong>Course 28</strong>: Excel: Top 50 Microsoft Excel Formulas in 50 Minutes!</li><li><strong>Course 29</strong>: Decision-Making and Critical Thinking</li><li><strong>Course 30</strong>: Time Management Training - Online Course</li></ul><p><strong>What will make you stand out?</strong></p><p>Upon completion of this online IT Security: CompTIA network+ with SQL -(30 in 1 Bundle) , you will gain the following:</p><ul><li>CPD QS Accredited Proficiency with this IT Security: CompTIA network+ with SQL  Bundle </li><li>After successfully completing the IT Security: CompTIA network+ with SQL    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 IT Security: CompTIA network+ with SQL Bundle</li><li>The online test with immediate results </li><li>You can study and complete the IT Security: CompTIA network+ with SQL bundle at your own pace.</li><li>Study for the IT Security: CompTIA network+ with SQL bundle using any internet-connected device, such as a computer, tablet, or mobile device.</li></ul><p>The IT Security: CompTIA network+ with SQL -(30 in 1 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 IT Security: CompTIA network+ with SQL bundle, a comprehensive, complete collection of 30 courses. Each course in the IT Security: CompTIA network+ with SQL 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  IT Security: CompTIA network+ with SQL  bundle offers the flexibility and convenience to learn at your own pace. Make the  IT Security: CompTIA network+ with SQL 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 IT Security: CompTIA network+ with SQL -(30 in 1 Bundle)  is perfect for:</p><ul><li>Expand your knowledge and skillset for a fulfilling career with IT Security: CompTIA network+ with SQL    bundle.</li><li>Become a more valuable professional by earning CPD certification and mastering in-demand skills with the IT Security: CompTIA network+ with SQL bundle.</li><li>Discover your passion or explore new career options with the diverse learning opportunities in the IT Security: CompTIA network+ with SQL bundle.</li><li>Learn on your schedule, in the comfort of your home - the IT Security: CompTIA network+ with SQL  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 IT Security: CompTIA network+ with SQL  bundle.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

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

                        </div>

Compliance Central

Cloud Computing: CompTIA Cloud+ & Cyber Security- 30 CPD Certified Courses!

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

Nexus Human

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

Azure Machine Learning

Microsoft AI-900

AI-900T00 Microsoft Azure AI Fundamentals

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

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

Microsoft AZ-104

Azure Cognitive Services

AI-102T00 Designing and Implementing an Azure AI Solution

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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>

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