Overview What You Will Learn Curriculum Instructor

Course Overview

Advanced machine learning has become a crucial asset for business professionals looking to harness data-driven decision-making. Understanding machine learning concepts, techniques, and applications enables professionals to unlock valuable insights, improve efficiency, and drive innovation. While artificial intelligence (AI) broadly encompasses intelligent systems, machine learning (ML) focuses on training models to recognize patterns and make predictions. This course equips business professionals with the foundational knowledge needed to effectively engage with ML teams, make informed strategic decisions, and leverage ML solutions in their organizations.

This course begins with an introduction to machine learning, differentiating it from AI and exploring essential ML terminology. It then delves into supervised and unsupervised learning techniques, covering classification, regression, recommender systems, and reinforcement learning. Learners will gain insights into the ML workflow, from defining problems to building functional solutions. The course also covers data preprocessing in natural language processing, computer vision, and structured data. Participants will learn how to train, test, and evaluate models using appropriate metrics for classification, regression, and unsupervised learning. Finally, the course explores ML deployment, maintenance, ethical considerations, team structures, and best practices for working with ML teams.

By the end of this course, business professionals will have a comprehensive understanding of machine learning principles, workflows, and real-world applications, empowering them to effectively implement ML strategies and collaborate with technical teams.

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

  • 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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