AI
Intermediate
AI & ML
Machine Learning with Python
This comprehensive course will take you from beginner to confident practitioner in Machine Learning with Python. You'll learn industry-standard techniques and best practices used by professionals worldwide.\\n\\nThrough hands-on projects and real-world examples, you'll gain the skills needed to succeed in today's competitive tech landscape. Our curriculum is designed by industry experts with years of experience.\\n\\nBy the end of this course, you'll have a portfolio of projects to showcase your abilities and the confidence to apply your knowledge in professional settings.
Course Syllabus
Week 1: Introduction to AI Concepts
- Lesson 1: Advanced Tensors Techniques Preview 14min
- Lesson 2: Gradient Descent Explained Preview 22min
- Lesson 3: Practical Neurons 8min
- Lesson 4: Working with Tensors 19min
- Lesson 5: Deep Dive into Feature Engineering 18min
- Lesson 6: Building Gradient Descent 17min
Week 2: Data Preparation & Cleaning
- Lesson 1: Neurons Explained 16min
- Lesson 2: Neurons Explained 23min
- Lesson 3: Practical Tensors 14min
- Lesson 4: Practical Neurons 16min
- Lesson 5: Advanced Gradient Descent Techniques 12min
- Lesson 6: Feature Engineering Fundamentals 25min
Week 3: Building Your First Model
- Lesson 1: Working with Classification 14min
- Lesson 2: Understanding Neurons 21min
- Lesson 3: Tensors Best Practices 9min
- Lesson 4: Working with Tensors 15min
- Lesson 5: Working with Overfitting 13min
Week 4: Training & Evaluation
- Lesson 1: Building Feature Engineering 18min
- Lesson 2: Working with Gradient Descent 9min
- Lesson 3: Feature Engineering Best Practices 9min
- Lesson 4: Building Classification 18min
- Lesson 5: Gradient Descent Explained 13min