Overview What You Will Learn Curriculum Instructor

Course Overview

Machine Learning, often called AI, is one of the most innovative areas of technology. Over the last few years, it has revolutionized our society with novelties such as automated cars, facial recognition, and language translations.

You have heard about the power of ML but you do not know how it can bring value to your organization? Do you wish to learn how ML is used for automation, predictions, analysis, and better decisions making? 

If you want your organization to become better at using AI, this course is for you! In this course, you will understand the concept of ML, all the benefits of using ML, and how ML projects can be implemented in your business. 

We will explore different applications of ML that will help you uncover all the opportunities ML can bring to your organization. 

This course will give you all the skills to harness the power of AI.

What You Will Learn

  • AI and Machine Learning terminology (supervised learning
  • unsupervised learning
  • classification …)
  • The most advanced Machine Learning techniques and their use cases
  • The importance of an R&D or a Proof-of-Concept phase in an ML project
  • How to move on from a prototype to a fully functional solution
  • Identify the opportunities to apply AI within your organization
  • The different roles involved in an AI and ML project
  • their skills and their technical tools

Program Curriculum

  • What is Machine Learning?
  • Difference Between ML and AI
  • The Terminology of Machine Learning
  • $7 Million Cybersecurity Scholarship by EC-Council
  • Chapter 1 Quiz

  • Introduction to Supervised Learning
  • Classification with Decision Trees
  • Regression with Linear Regression
  • Introduction to Unsupervised Learning
  • Recommender System with Unsupervised Learning
  • Introduction to Reinforcement Learning
  • Chapter 2 Quiz

  • Define the Problem
  • Collect and Evaluate the Data
  • The R&D Phase
  • Build a Functional Solution
  • Chapter 3 Quiz

  • Text Preprocessing in Natural Language Processing
  • Image Preprocessing in Computer Vision
  • Data Preprocessing for Categorical and Continuous Variables
  • Chapter 4 Quiz

  • Training and Testing on Different Data
  • Metrics to Evaluate a Classification Model
  • Metrics to Evaluate a Regression Model
  • How to Evaluate Unsupervised Learning Models
  • Chapter 5 Quiz

  • How to Deploy ML Models
  • How to Evaluate a Model in Production
  • How to Improve the Performance of a Model
  • Chapter 6 Quiz

  • Identify the Right Machine Learning Project for Your Business
  • What Machine Learning Can Do and Cannot Do
  • Ethics in Machine Learning
  • Chapter 7 Quiz
  • test

  • Different Roles and Functions in a ML Team
  • How to Work with a ML Team
  • Technical Tools Used by a ML Team
  • Conclusion
Load more modules

Instructor

Wassim Ben Youssef

Wassim Ben Youssef has 4 years of experience in Data Science and applied Machine Learning. He has worked as a Data Scientist for several fintech startups in London, helping them to build their Data Science team and develop and deploy Machine Learning models into their products. He is also a teaching assistant for a company providing Data Science Bootcamps. Passionate and excited about how AI can change the world, Wassim likes to stay connected with the Data Science community and informed of the new cutting-edge applications of AI by attending events such as the Data Science Festival or CognitionX. Wassim holds several Master degrees in Data Science, Applied Mathematics and Computer Science.

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