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Overview This comprehensive course on Data Science & Machine Learning with R will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with R comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Science & Machine Learning with R. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with R is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 10 sections • 69 lectures • 22:07:00 total length •Data Science and Machine Learning Introduction: 00:03:00 •What is Data Science: 00:10:00 •Machine Learning Overview: 00:05:00 •Who is This Course for: 00:03:00 •Data Science and Machine Learning Marketplace: 00:05:00 •Data Science and Machine Learning Job Opportunities: 00:03:00 •Getting Started: 00:11:00 •Basics: 00:06:00 •Files: 00:11:00 •RStudio: 00:07:00 •Tidyverse: 00:05:00 •Resources: 00:04:00 •Unit Introduction: 00:30:00 •Basic Type: 00:09:00 •Vector Part One: 00:20:00 •Vectors Part Two: 00:25:00 •Vectors - Missing Values: 00:16:00 •Vectors - Coercion: 00:14:00 •Vectors - Naming: 00:10:00 •Vectors - Misc: 00:06:00 •Creating Matrics: 00:31:00 •List: 00:32:00 •Introduction to Data Frames: 00:19:00 •Creating Data Frames: 00:20:00 •Data Frames: Helper Functions: 00:31:00 •Data Frames Tibbles: 00:39:00 •Intermediate Introduction: 00:47:00 •Relational Operations: 00:11:00 •Conditional Statements: 00:11:00 •Loops: 00:08:00 •Functions: 00:14:00 •Packages: 00:11:00 •Factors: 00:28:00 •Dates and Times: 00:30:00 •Functional Programming: 00:37:00 •Data Import or Export: 00:22:00 •Database: 00:27:00 •Data Manipulation in R Introduction: 00:36:00 •Tidy Data: 00:11:00 •The Pipe Operator: 00:15:00 •The Filter Verb: 00:22:00 •The Select Verb: 00:46:00 •The Mutate Verb: 00:32:00 •The Arrange Verb: 00:10:00 •The Summarize Verb: 00:23:00 •Data Pivoting: 00:43:00 •JSON Parsing: 00:11:00 •String Manipulation: 00:33:00 •Web Scraping: 00:59:00 •Data Visualization in R Section Intro: 00:17:00 •Getting Started: 00:16:00 •Aesthetics Mappings: 00:25:00 •Single Variable Plots: 00:37:00 •Two Variable Plots: 00:21:00 •Facets, Layering, and Coordinate Systems: 00:18:00 •Styling and Saving: 00:12:00 •Creating with R Markdown: 00:29:00 •Introduction to R Shiny: 00:26:00 •A Basic R Shiny App: 00:31:00 •Other Examples with R Shiny: 00:34:00 •Machine Learning Part 1: 00:22:00 •Machine Learning Part 2: 00:47:00 •Starting a Data Science Career Section Overview: 00:03:00 •Data Science Resume: 00:04:00 •Getting Started with Freelancing: 00:05:00 •Top Freelance Websites: 00:05:00 •Personal Branding: 00:05:00 •Importance of Website and Blo: 00:04:00 •Networking Do's and Don'ts: 00:04:00

Overview In this age of technology, data science and machine learning skills have become highly demanding skill sets. In the UK a skilled data scientist can earn around £62,000 per year. If you are aspiring for a career in the IT industry, secure these skills before you start your journey. The Complete Machine Learning & Data Science Bootcamp 2023 course can help you out. This course will introduce you to the essentials of Python. From the highly informative modules, you will learn about NumPy, Pandas and matplotlib. The course will help you grasp the skills required for using python for data analysis and visualisation. After that, you will receive step-by-step guidance on Python for machine learning. The course will then focus on the concepts of Natural Language Processing.  Upon successful completion of the course, you will receive a certificate of achievement. This certificate will help you elevate your resume. So enrol today! How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? Anyone with an interest in learning about data science can enrol in this course. It will help aspiring professionals develop the basic skills to build a promising career. Professionals already working in this can take the course to improve their skill sets. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush.   Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst Course Curriculum 18 sections • 98 lectures • 23:48:00 total length •Welcome & Course Overview6: 00:07:00 •Set-up the Environment for the Course (lecture 1): 00:09:00 •Set-up the Environment for the Course (lecture 2): 00:25:00 •Two other options to setup environment: 00:04:00 •Python data types Part 1: 00:21:00 •Python Data Types Part 2: 00:15:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1): 00:16:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2): 00:20:00 •Python Essentials Exercises Overview: 00:02:00 •Python Essentials Exercises Solutions: 00:22:00 •What is Numpy? A brief introduction and installation instructions.: 00:03:00 •NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes.: 00:28:00 •NumPy Essentials - Indexing, slicing, broadcasting & boolean masking: 00:26:00 •NumPy Essentials - Arithmetic Operations & Universal Functions: 00:07:00 •NumPy Essentials Exercises Overview: 00:02:00 •NumPy Essentials Exercises Solutions: 00:25:00 •What is pandas? A brief introduction and installation instructions.: 00:02:00 •Pandas Introduction: 00:02:00 •Pandas Essentials - Pandas Data Structures - Series: 00:20:00 •Pandas Essentials - Pandas Data Structures - DataFrame: 00:30:00 •Pandas Essentials - Handling Missing Data: 00:12:00 •Pandas Essentials - Data Wrangling - Combining, merging, joining: 00:20:00 •Pandas Essentials - Groupby: 00:10:00 •Pandas Essentials - Useful Methods and Operations: 00:26:00 •Pandas Essentials - Project 1 (Overview) Customer Purchases Data: 00:08:00 •Pandas Essentials - Project 1 (Solutions) Customer Purchases Data: 00:31:00 •Pandas Essentials - Project 2 (Overview) Chicago Payroll Data: 00:04:00 •Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data: 00:18:00 •Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach: 00:13:00 •Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials - Exercises Overview: 00:06:00 •Matplotlib Essentials - Exercises Solutions: 00:21:00 •Seaborn - Introduction & Installation: 00:04:00 •Seaborn - Distribution Plots: 00:25:00 •Seaborn - Categorical Plots (Part 1): 00:21:00 •Seaborn - Categorical Plots (Part 2): 00:16:00 •Seborn-Axis Grids: 00:25:00 •Seaborn - Matrix Plots: 00:13:00 •Seaborn - Regression Plots: 00:11:00 •Seaborn - Controlling Figure Aesthetics: 00:10:00 •Seaborn - Exercises Overview: 00:04:00 •Seaborn - Exercise Solutions: 00:19:00 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1): 00:19:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2): 00:14:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview): 00:11:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions): 00:17:00 •Project 1 - Oil vs Banks Stock Price during recession (Overview): 00:15:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3): 00:17:00 •Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview): 00:03:00 •Introduction to ML - What, Why and Types..: 00:15:00 •Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff: 00:15:00 •scikit-learn - Linear Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Linear Regression Model Hands-on (Part 2): 00:19:00 •Good to know! How to save and load your trained Machine Learning Model!: 00:01:00 •scikit-learn - Linear Regression Model (Insurance Data Project Overview): 00:08:00 •scikit-learn - Linear Regression Model (Insurance Data Project Solutions): 00:30:00 •Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc.: 00:10:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 2): 00:20:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 3): 00:11:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Overview): 00:05:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Solutions): 00:15:00 •Theory: K Nearest Neighbors, Curse of dimensionality .: 00:08:00 •scikit-learn - K Nearest Neighbors - Hands-on: 00:25:00 •scikt-learn - K Nearest Neighbors (Project Overview): 00:04:00 •scikit-learn - K Nearest Neighbors (Project Solutions): 00:14:00 •Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging.: 00:18:00 •scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1): 00:19:00 •scikit-learn - Decision Tree and Random Forests (Project Overview): 00:05:00 •scikit-learn - Decision Tree and Random Forests (Project Solutions): 00:15:00 •Support Vector Machines (SVMs) - (Theory Lecture): 00:07:00 •scikit-learn - Support Vector Machines - Hands-on (SVMs): 00:30:00 •scikit-learn - Support Vector Machines (Project 1 Overview): 00:07:00 •scikit-learn - Support Vector Machines (Project 1 Solutions): 00:20:00 •scikit-learn - Support Vector Machines (Optional Project 2 - Overview): 00:02:00 •Theory: K Means Clustering, Elbow method.: 00:11:00 •scikit-learn - K Means Clustering - Hands-on: 00:23:00 •scikit-learn - K Means Clustering (Project Overview): 00:07:00 •scikit-learn - K Means Clustering (Project Solutions): 00:22:00 •Theory: Principal Component Analysis (PCA): 00:09:00 •scikit-learn - Principal Component Analysis (PCA) - Hands-on: 00:22:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Overview): 00:02:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Solutions): 00:17:00 •Theory: Recommender Systems their Types and Importance: 00:06:00 •Python for Recommender Systems - Hands-on (Part 1): 00:18:00 •Python for Recommender Systems - - Hands-on (Part 2): 00:19:00 •Natural Language Processing (NLP) - (Theory Lecture): 00:13:00 •NLTK - NLP-Challenges, Data Sources, Data Processing ..: 00:13:00 •NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing: 00:19:00 •NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW.: 00:19:00 •NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes : 00:13:00 •NLTK - NLP - Pipeline feature to assemble several steps for cross-validation: 00:09:00

Overview This comprehensive course on Assembly Programming For All Platforms will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Assembly Programming For All Platforms comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast-track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Assembly Programming For All Platforms. It is available to all students, of all academic backgrounds. Requirements Our Assembly Programming For All Platforms is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 13 sections • 48 lectures • 02:07:00 total length •Introduction: 00:02:00 •Project Setup: 00:02:00 •Example File Code Structure: 00:02:00 •Comments: 00:03:00 •Memory Segments: 00:02:00 •Processor Registers: 00:04:00 •Data Registers: 00:04:00 •Pointer Registers: 00:02:00 •Index Registers: 00:01:00 •Control Registers: 00:04:00 •Segment Registers: 00:01:00 •Register Addressing: 00:04:00 •Immediate Addressing Mode: 00:02:00 •Direct Memory Addressing Mode: 00:02:00 •Direct-Offset Addressing Mode: 00:03:00 •Indirect Memory Addressing Mode: 00:02:00 •MOV Instruction: 00:02:00 •Allocating Storage Space for Initialised Data: 00:04:00 •Allocating Storage Space for Uninitialized Data: 00:02:00 •Multiple Variable Definitions: 00:02:00 •Multiple Variable Initialisations: 00:03:00 •EQU Command: 00:03:00 •Assign Command: 00:02:00 •Define Command: 00:02:00 •Increment Command (INC): 00:02:00 •Decrement Command (DEC): 00:02:00 •Addition Command (ADD): 00:03:00 •Subtraction Command (SUB): 00:02:00 •Multiply Command (MUL/IMUL): 00:02:00 •Divide Command (DIV/IDIV): 00:03:00 •AND Instruction: 00:04:00 •OR Instruction: 00:03:00 •XOR Instruction: 00:03:00 •NOT Instruction: 00:02:00 •Compare Instruction (CMP): 00:02:00 •Unconditional Jump: 00:02:00 •Conditional Jump: 00:03:00 •ASCII System: 00:02:00 •Basic Function: 00:03:00 •Stacks Data Structure: 00:04:00 •Function To Print Number: 00:05:00 •Recursion Using Factorial: 00:06:00 •Strings: 00:04:00 •Loops: 00:03:00 •Macros: 00:03:00 •System Calls: 00:04:00 •Resource: 00:00:00 •Assignment - Assembly Programming For All Platforms: 00:00:00

Course Overview: Dive into the transformative world of Artificial Intelligence (AI) with "ChatGPT for Marketing and Productivity with AI Tools. This course is tailored to unlock the secrets of AI-powered tools in marketing and productivity. According to the McKinsey Global Institute, Artificial Intelligence is an area of study predicted to have an economic impact between $1.49 trillion to $2.95 trillion a year by 2025. It's time to leverage this transformative technology with OpenAI's ChatGPT. In this course, we'll start from the basics, introducing you to OpenAI's ChatGPT, its features, limitations, and how to create an account. You will learn how ChatGPT can generate ideas, qualify and verify information, and produce content in different contexts. In addition, you'll explore a myriad of autonomous AI agents and learn to develop robust methodologies with expert advice. The last part of the course delves into tools and applications like Bing Search, Google Bard, and Speechify that you can use in tandem with ChatGPT. By the end of this course, you'll be well-versed in harnessing the power of AI to enhance marketing strategies and improve productivity. Enrol now and stay ahead of the competition! Key Features of the Course: CPD-certified course. 24/7 learning assistance. Engaging learning materials to enhance your knowledge. Updated and trending content. Who is This Course For? This ChatGPT for Marketing and Productivity with AI Tools course is ideal for marketing professionals, content creators, product managers, or anyone interested in leveraging AI to improve productivity and marketing strategies. What You Will Learn: Our comprehensive ChatGPT for Marketing and Productivity with AI Tools course will help you to: Understanding and setting up an account with ChatGPT. Exploring the limitations and potentials of ChatGPT. The use of ChatGPT in idea generation, content creation, and problem-solving. Interfacing with autonomous AI agents. Use of AI tools for research, summarisation, and voice cloning. Manipulating Microsoft Bing Search, Google Bard, and other applications with ChatGPT. Insight into the future of Generative AI. How to use ChatGPT to conduct research. Why Enrol in This Course: This top-reviewed and recently updated course allows learners to stay at the forefront of the AI revolution. You will gain a competitive edge by developing skills in AI applications for marketing and productivity. Requirements: Participants are expected to have a basic understanding of marketing and productivity processes. Prior experience with AI is not necessary. Career Path: AI Product Manager - £75,000. Content Strategist - £42,000. Marketing Technology Consultant - £60,000. Digital Marketer - £32,000. SEO Specialist - £35,000. Social Media Manager - £45,000. Data Analyst - £40,000. Certification: Upon completing the ChatGPT for Marketing and Productivity with AI Tools course, you will receive a CPD certificate, validating your newly acquired skills and knowledge. Enrol in this course today and enhance your Marketing and Productivity with AI Tools! Course Curriculum 3 sections • 60 lectures • 01:24:00 total length •Unit 01: Start an Account with ChatGPT: 00:02:00 •Unit 02: What the Company OpenAI Say About Itself: 00:02:00 •Unit 03: What OpenAI Say About The Limitations of the Chatbot: 00:02:00 •Unit 04: Chatbot Prompt Examples Given By Open AI: 00:02:00 •Unit 05: Will Chat GPT Be a Paid Application: 00:01:00 •Unit 06: Chat GPT Idea Generation: 00:02:00 •Unit 07: Chat GPT - Idea Qualification and Accuracy: 00:03:00 •Unit 08: ChatGPT - Accuracy and Citations: 00:02:00 •Unit 09: Chat GPT - Creating HTML Instances: 00:01:00 •Unit 10: Chat GPT - How to Solve Specific Business Problems: 00:02:00 •Unit 11: Chat GPT - Statistical Verification of Information: 00:01:00 •Unit 12: Chat GPT - Rewrite Content for Different Contexts: 00:02:00 •Unit 13: ChatGPT - Content Checked With AI: 00:02:00 •Unit 14: ChatGPT - Simplifying Information: 00:01:00 •Unit 15: ChatGPT - How to Ask the Chatbot about Context: 00:01:00 •Unit 16: ChatGPT - How to Cross-Post Queries: 00:01:00 •Unit 17: ChatGPT - How to Narrow Down the Context of Your Query: 00:02:00 •Unit 18: ChatGPT - How to Solve a Business Process: 00:02:00 •Unit 19: ChatGPT - Developing a Methodology From Experts: 00:01:00 •Unit 20: The Future of ChatGPT: 00:01:00 •Unit 01: Autonous AI Agents: 00:01:00 •Unit 02: Connecting to Open AI: 00:01:00 •Unit 03: Getting an OpenAI Key: 00:01:00 •Unit 04: Agent GPT - Autonomous AI: 00:02:00 •Unit 05: GoalGPT - Autonomous Agents: 00:01:00 •Unit 06: Cognosis - Autonomous AI: 00:02:00 •Unit 07: Aomni - Autonomous Agent: 00:01:00 •Unit 08: Durable - Build a Website with AI: 00:01:00 •Unit 09: Eightify Summaries: 00:02:00 •Unit 10: Genei - Do Higher Quality Research with AI: 00:01:00 •Unit 11: Ellicit - Do Higher Quality Research with AI: 00:01:00 •Unit 12: Inciteful - Do Higher Quality Research with AI: 00:02:00 •Unit 13: SciteAI Determine the Credibility of Your Research: 00:01:00 •Unit 14: Eleven Labs - Voice Cloning: 00:02:00 •Unit 15: AgentGPT - Wrap Up and Return: 00:01:00 •Unit 16: Cognosys - Wrap Up and Return: 00:01:00 •Unit 17: Aomni - Wrap Up and Return: 00:01:00 •Unit 18: Goal GPT - Wrap Up and Return: 00:01:00 •Unit 19: Uploading Research Reports to Summarization Applications: 00:01:00 •Unit 20: Perspective on The Future of AI: 00:01:00 •Unit 01: Meta Search Sites: 00:02:00 •Unit 02: SMMRY for Summarzing: 00:01:00 •Unit 03: ChatGPT Plugins Waitlist: 00:01:00 •Unit 04: Using Microsoft Bing Search: 00:02:00 •Unit 05: Using Google Bard: 00:01:00 •Unit 06: Microsoft Word Speech To Text: 00:01:00 •Unit 07: Transcribe Audio in Microsoft Word: 00:02:00 •Unit 08: Speechify: 00:02:00 •Unit 09: Exact Image Creation: 00:01:00 •Unit 10: AI Design Tools: 00:02:00 •Unit 11: Learn How to Prompt: 00:01:00 •Unit 12: Content Improvement: 00:01:00 •Unit 13: Idea Generation: 00:01:00 •Unit 14: Audio Enhancement with Adobe: 00:02:00 •Unit 15: Clean up Audio With Cleaanvoice: 00:01:00 •Unit 16: Notion-AI: 00:01:00 •Unit 17: Pictory: 00:01:00 •Unit 18: Lex: 00:01:00 •Unit 19: ChatPDF: 00:01:00 •Unit 20: Conclusion and the Future of Generatie AI - Searchie: 00:01:00

Overview This comprehensive course on Quick Data Science Approach from Scratch will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Quick Data Science Approach from Scratch comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Quick Data Science Approach from Scratch. It is available to all students, of all academic backgrounds. Requirements Our Quick Data Science Approach from Scratch is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 4 sections • 15 lectures • 01:00:00 total length •Introduction: 00:02:00 •Data Science Explanation: 00:05:00 •Need of Data Science: 00:02:00 •8 Common mistakes by Aspiring Data Scientists/Data Science Enthusiasts: 00:08:00 •Myths about Data Science: 00:03:00 •Data Types and Variables: 00:04:00 •Descriptive Analysis: 00:02:00 •Data Cleaning: 00:02:00 •Feature Engineering: 00:02:00 •Data Thinking Development: 00:03:00 •Problem Definition: 00:05:00 •Algorithms: 00:14:00 •Prediction: 00:03:00 •Learning Methods: 00:05:00 •Assignment - Quick Data Science Approach from Scratch: 00:00:00

Overview This comprehensive course on Maya & Unity 3D: Modeling Environments for Mobile Games will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Maya & Unity 3D: Modeling Environments for Mobile Games comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Maya & Unity 3D: Modeling Environments for Mobile Games. It is available to all students, of all academic backgrounds. Requirements Our Maya & Unity 3D: Modeling Environments for Mobile Games is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 2 sections • 13 lectures • 01:59:00 total length •Module 01: Get To Know Your Instructor and the Course: 00:02:00 •Module 02: Modeling the Base of the Island: 00:17:00 •Module 03: Modeling the Buildings: 00:36:00 •Module 04: Unwrap, Texture And Apply Materials: 00:14:00 •Module 05: Add Flowers, Birds and Background: 00:13:00 •Module 06: Export the Models from Maya to Unity: 00:05:00 •Module 07: Import and Setup the Project in Unity: 00:04:00 •Module 08: Add Our Mesh to the Scene: 00:05:00 •Module 09: Materials and Textures: 00:06:00 •Module 10: Setup Camera and Lightning: 00:06:00 •Module 11: Bake the Light Map: 00:08:00 •Module 12: Add Camera Effect to Polish the Scene: 00:03:00 •Assignment - Maya & Unity 3D: Modeling Environments for Mobile Games: 00:00:00

Overview This comprehensive course on Master JavaScript with Data Visualization will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Master JavaScript with Data Visualization comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Master JavaScript with Data Visualization. It is available to all students, of all academic backgrounds. Requirements Our Master JavaScript with Data Visualization is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 11 sections • 76 lectures • 06:21:00 total length •Introduction to Getting Started: 00:02:00 •Course Curriculum: 00:05:00 •How to Get Pre-Requisites: 00:02:00 •Getting Started on Windows, Linux or Mac: 00:01:00 •How to ask a Great Questions: 00:02:00 •FAQ's: 00:01:00 •What is JavaScript: 00:09:00 •Choosing Code Editor: 00:03:00 •Installing Code Editor (Sublime Text): 00:04:00 •Installing Code Editor(Visual Studio Code): 00:07:00 •Hello World Program: 00:14:00 •Getting Output: 00:11:00 •Summary: 00:02:00 •Introduction: 00:02:00 •Internal JavaScript: 00:13:00 •External JavaScript: 00:09:00 •Inline JavaScript: 00:04:00 •Async and defer: 00:06:00 •Variables: 00:13:00 •Data Types: 00:10:00 •Numbers: 00:06:00 •Boolean: 00:04:00 •Arrays(): 00:12:00 •Objects: 00:06:00 •Comments: 00:05:00 •Summary: 00:01:00 •Introduction: 00:02:00 •Strings: 00:06:00 •String Formatting: 00:05:00 •String Methods: 00:12:00 •Summary: 00:02:00 •Introduction: 00:02:00 •Arithmetic operators: 00:07:00 •Assignment operators: 00:03:00 •Comparison operators: 00:06:00 •Logical operators: 00:08:00 •Summary: 00:02:00 •Introduction: 00:02:00 •If statement: 00:04:00 •If-else statement: 00:05:00 •If-else-if statement: 00:04:00 •Switch-case statement: 00:09:00 •Summary: 00:01:00 •Introduction: 00:02:00 •While loop: 00:09:00 •Do-while loop: 00:03:00 •For loop: 00:08:00 •Break: 00:02:00 •Continue: 00:03:00 •Coding Exercise: 00:02:00 •Solution for Coding Exercise: 00:02:00 •Summary: 00:02:00 •Introduction: 00:02:00 •Creating a Function: 00:07:00 •Function Call(): 00:07:00 •Function with parameters: 00:05:00 •Function Bind(): 00:06:00 •Summary: 00:01:00 •Introduction: 00:01:00 •How to Use Google chart script: 00:04:00 •Line Graph chart: 00:14:00 •Scatter plots chart: 00:02:00 •Bar chart: 00:04:00 •Pie chart: 00:02:00 •3D Pie chart: 00:02:00 •Summary: 00:01:00 •Introduction: 00:01:00 •Try-catch: 00:05:00 •Try-catch-finally: 00:17:00 •Summary: 00:01:00 •Introduction: 00:01:00 •On Submit Validation: 00:09:00 •Input Numeric Validation: 00:12:00 •Login Form Validation: 00:05:00 •Password Strength Check Validation: 00:04:00 •Summary: 00:01:00

Anti-Money Laundering (AML): This comprehensive Anti-Money Laundering (AML) course is designed for individuals interested in safeguarding organizations against financial crime. Through up-to-date knowledge and practical guidance, you will be trained in the essential skills required to identify and prevent suspicious activities within any organization. With step-by-step instructions on conducting client risk assessments, this course equips you with a strong foundation in AML procedures.

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