About This Course
Artificial Intelligence and Machine Learning (AI/ML) are transforming industries by enabling computers to learn from data and make intelligent decisions. This course provides a comprehensive, hands-on introduction to AI and Machine Learning using Python, covering core concepts such as supervised learning, unsupervised learning, clustering, recommendation systems, and real-world model development.
You will learn how to work with data, train machine learning models, and apply AI techniques to solve practical business problems. Through real-world examples, projects, and practical exercises, students will gain industry-ready skills required for roles like Machine Learning Engineer, Data Analyst, and AI Developer.
Whether you are a beginner, student, or working professional, this course will help you build strong AI/ML foundations and practical experience using modern tools and frameworks widely used in the industry.
By the end of this course, you will be able to build, evaluate, and deploy machine learning models confidently.
Learning Objectives
Material Includes
- Video lessons with practical demonstrations
- Hands-on projects and practice exercises
- Downloadable code, datasets, and learning resources
- Quizzes and course completion certificate
Target Audience
- Beginners and students interested in AI, ML, and Data Science
- Job seekers preparing for AI, ML, or Data Analyst roles
- Developers and IT professionals upgrading to AI/ML skills
- Career switchers entering high-demand technology fields
Curriculum
Module 1: Introduction to Artificial Intelligence & Machine Learning
Introduction to Artificial Intelligence
Introduction to Machine Learning
AI vs Machine Learning vs Deep Learning
Relationship between AI and Machine Learning
Data Science and Machine Learning
Module 2: Machine Learning Concepts
Module 3: Supervised Learning
Module 4: Unsupervised Learning
Module 5: Recommendation Systems
Module 6: Introduction to Python
Module 7: Python Programming for Machine Learning
