997 Data Science courses

Want to learn everything about Python, from installing to coding, with a liberal does of fun sprinkled into the learning? Then, this Python Programming Tutorials For Beginners is what you need.

This course will help you get started with automation testing of web applications. You will cover the basic and advanced topics of Selenium and Python, along with unit tests, pytest, cross-browser testing, logging infrastructure, automation framework design, Jenkins, and a lot more.

Take your Python coding skills to the next level with our Intermediate Python Coding Course. Dive deeper into the language's capabilities, mastering advanced concepts and techniques to tackle complex programming challenges. Whether you're a beginner looking to expand your knowledge or an experienced coder seeking to enhance your proficiency, this course offers comprehensive instruction and hands-on practice to help you advance your Python skills. Enroll now and level up your coding abilities with confidence.

Description:  The significance of Big Data in terms of web presence and advertisement is very important to reach out to your customers and potential customers. In this course, you will learn how to tweak your account to achieve the maximum result. By the end of this course, you will learn about the marketing tips, traffic, tools, and add-on that could help in your success. Who is the course for? Professionals who want to learn how to become profitable through Twitter Social Marketing People who have an interest in Social Marketing and promote through Twitter Entry Requirement: This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Assessment: At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at a cost of £39 or in PDF format at a cost of £24. PDF certificate's turnaround time is 24 hours and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognised accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path: The Understanding Big Data Course will be very beneficial and helpful, especially to the following careers: Businessman Marketing and Promotions Specialist Marketing Manager Online Content Creator Sales Manager Sales and Promotions Specialist Social Media Specialist. Understanding Big Data What Is Big Data? Hint: You're a Part of It Every Day 01:00:00 Why Is Big Data Important? 01:00:00 Why IBM for Big Data? 01:00:00 All About Hadoop: The Big Data Lingo Chapter 01:00:00 InfoSphere BigInsights: Analytics for Big Data at Rest 01:00:00 IBM InfoSphere Streams: Analytics for Big Data in Motion 01:00:00 Mock Exam Mock Exam-Understanding Big Data 00:20:00 Final Exam Final Exam-Understanding Big Data 00:20:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Overview This comprehensive course on Python for Data Analysis will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Python for Data Analysis 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 Python for Data Analysis. It is available to all students, of all academic backgrounds. Requirements Our Python for Data Analysis 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 19 sections • 99 lectures • 00:08:00 total length •Welcome & Course Overview: 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): 00:37:00 •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 •Resources- Python for Data Analysis: 00:00:00

This course covers the Django web framework from the beginning and also covers advanced Django features. Besides Django, the course also covers HTML, CSS, and Bootstrap, which will introduce full-stack development with Django so that you can build complete web apps from scratch. Learn to develop your own web applications with the help of this course.

Overview This comprehensive course on Building Big Data Pipelines with PySpark MongoDB and Bokeh will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Building Big Data Pipelines with PySpark MongoDB and Bokeh 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 Building Big Data Pipelines with PySpark MongoDB and Bokeh. It is available to all students, of all academic backgrounds. Requirements Our Building Big Data Pipelines with PySpark MongoDB and Bokeh 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 7 sections • 25 lectures • 05:04:00 total length •Introduction: 00:10:00 •Python Installation: 00:03:00 •Installing Third Party Libraries: 00:03:00 •Installing Apache Spark: 00:12:00 •Installing Java (Optional): 00:05:00 •Testing Apache Spark Installation: 00:06:00 •Installing MongoDB: 00:04:00 •Installing NoSQL Booster for MongoDB: 00:07:00 •Integrating PySpark with Jupyter Notebook: 00:05:00 •Data Extraction: 00:19:00 •Data Transformation: 00:15:00 •Loading Data into MongoDB: 00:13:00 •Data Pre-processing: 00:19:00 •Building the Predictive Model: 00:12:00 •Creating the Prediction Dataset: 00:08:00 •Loading the Data Sources from MongoDB: 00:17:00 •Creating a Map Plot: 00:33:00 •Creating a Bar Chart: 00:09:00 •Creating a Magnitude Plot: 00:15:00 •Creating a Grid Plot: 00:09:00 •Installing Visual Studio Code: 00:05:00 •Creating the PySpark ETL Script: 00:24:00 •Creating the Machine Learning Script: 00:30:00 •Creating the Dashboard Server: 00:21:00 •Source Code and Notebook: 00:00:00

Artificial neural networks (ANNs) are the most powerful machine learning algorithms available today. They are capable of learning complex relationships in data, and they have been used to achieve state-of-the-art results in a wide variety of fields, including image recognition, natural language processing, and speech recognition. The Future of Machine Learning is Here! This Project on Deep Learning - Artificial Neural Network course will teach you how to build and train ANNs from scratch. You will learn about the different components of an ANN, such as the input layer, hidden layers, and output layer. You will also learn about the different activation functions that can be used in ANNs, and you will see how to optimise ANNs for different tasks. In addition to the theoretical concepts, you will also get experience with ANNs. You will work on a project where you will build an ANN to classify images. You will use the TensorFlow library to build your ANN, and you will see how to train your ANN on a dataset of images. By the end of this Project on Deep Learning - Artificial Neural Network course, you will have a deep understanding of ANNs and how to use them. You will be able to build your own ANNs to solve a variety of problems. You will also be able to use the TensorFlow library to build and train ANNs. So what are you waiting for? Enrol in this course today and start learning about the future of machine learning!   Learning Outcomes: Through this comprehensive course, you should be able to: Understand the fundamental concepts of deep learning and artificial neural networks. Install and configure an artificial neural network framework. Preprocess and structure data for optimal model performance. Encode data effectively for neural network training and predictions. Build and deploy artificial neural networks for real-world applications. Address data imbalance challenges and optimise model accuracy.   Who is this course for? This Project on Deep Learning - Artificial Neural Network course is ideal for: Data scientists and machine learning practitioners seeking to expand their knowledge. Software engineers interested in leveraging deep learning techniques. Students pursuing a career in artificial intelligence and machine learning. Professionals looking to enhance their skills in neural network development. Individuals with a passion for exploring advanced machine learning techniques.   Career Path  Our course will prepare you for a range of careers, including: Deep Learning Engineer: £40,000 - £100,000 per year. Machine Learning Researcher: £45,000 - £120,000 per year. Data Scientist: £50,000 - £110,000 per year. Artificial Intelligence Specialist: £55,000 - £130,000 per year. Software Engineer (specialising in AI): £45,000 - £100,000 per year. Research Scientist (Machine Learning): £50,000 - £120,000 per year. AI Consultant: £60,000 - £150,000 per year. Certification After studying the course materials of the Project on Deep Learning - Artificial Neural Network (ANNs) there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Prerequisites This Project on Deep Learning - Artificial Neural Network (ANNs) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Project on Deep Learning - Artificial Neural Network (ANNs) was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.   Course Curriculum Section 01: Introduction Introduction of Project 00:03:00 Section 02: ANN Installation Setup Environment for ANN 00:11:00 ANN Installation 00:09:00 Section 03: Data Preprocessing Import Libraries and Data Preprocessing 00:11:00 Data Preprocessing 00:07:00 Data Preprocessing Continue 00:10:00 Section 04: Data Encoding Data Exploration 00:10:00 Encoding 00:07:00 Encoding Continue 00:06:00 Preparation of Dataset for Training 00:04:00 Section 05: Steps to Build ANN Steps to Build ANN Part 1 00:06:00 Steps to Build ANN Part 2 00:06:00 Steps to Build ANN Part 3 00:06:00 Steps to Build ANN Part 4 00:09:00 Section 06: Predictions and Imbalance-Learn Predictions 00:11:00 Predictions Continue 00:08:00 Resampling Data with Imbalance-Learn 00:09:00 Resampling Data with Imbalance-Learn Continue 00:08:00

Overview of ChatGPT for Marketing and Productivity with AI Tools Visualise a world where artificial intelligence drives your marketing initiatives and AI tools revolutionise your business productivity. That's no longer just a fantasy; it's a reality you can be part of with our ChatGPT for Marketing and Productivity with AI Tools course. This industry has witnessed an explosion of opportunities, where those equipped with the knowledge to harness the power of artificial intelligence in marketing and productivity are at a significant advantage. Join us and become well-versed in using ChatGPT, one of the most sophisticated AI tools available. Learn how to seamlessly integrate Artificial Intelligence (AI) into your marketing strategies and enhance your productivity using AI tools. With this course, you are following the trend and becoming a trendsetter in the Artificial Intelligence (AI) marketing and productivity landscape. Join us and leap into the future with ChatGPT. This ChatGPT for Marketing and Productivity with AI Tools Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this ChatGPT for Marketing and Productivity with AI Tools. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the ChatGPT for Marketing and Productivity with AI Tools course, you can order your CPD Accredited Digital / PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This ChatGPT for Marketing and Productivity with AI Tools is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements There is no prerequisite to enrol in this course. You don't need any educational qualification or experience to enrol in the ChatGPT for Marketing and Productivity with AI Tools course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this ChatGPT for Marketing and Productivity with AI Tools Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Section 01: The AI Marketing Playbook 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 Section 02: How to Use ChatGPT and AI for Marketing 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 Section 03: Productivity with AI Tools 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 04: Using Microsoft Bing Search 00:02:00 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 With the ever-increasing demand for Data Analysis in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Data Analysis may be. Learning about Data Analysis or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Data Analysis. That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Data Analysis is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates. The self-paced online learning methodology by compete high in this Data Analysis Basics course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course! Instead of searching for hours, enrol right away on this Data Analysis Basics course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run.   Who is this course for? While we refrain from discouraging anyone wanting to do this Data Analysis Basics course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of Data Analysis, Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in Data Analysis, Anyone looking for a certificate of completion on doing an online training on this topic, Students of Data Analysis, or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity   Career Path This Data Analysis Basics course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams. Course Curriculum Module - 01 - Introduction to Data Analysis its Applications Introduction to Data Analysis its Applications 00:00 Module - 02 - Probability Probability Distributions Probability Probability Distributions 00:00 Module - 03 - Decision making and Factors to Account for Decision making and Factors to Account for 00:00 Module - 04 - Data Mining Data Mining 00:00 Module - 05 - Optimization Situation modelling Optimization Situation modelling 00:00