Intermediate

Computer Vision Basics

This comprehensive course will take you from beginner to confident practitioner in Computer Vision Basics. You'll learn industry-standard techniques and best practices used by professionals worldwide. Through 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. By 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.

Zainab Yusuf

Instructor

0 students 36 lessons Intermediate $149.99

Curriculum

Introduction to AI Concepts

Lesson 1: Gradient Descent Best Practices 18m

Lesson 2: Understanding Neurons 19m

Lesson 3: Mastering Tensors 18m

Lesson 4: Feature Engineering Fundamentals 9m

Data Preparation & Cleaning

Lesson 1: Advanced Gradient Descent Techniques 9m

Lesson 2: Tensors Fundamentals 21m

Lesson 3: Tensors Best Practices 19m

Lesson 4: Overfitting Fundamentals 20m

Lesson 5: Gradient Descent Fundamentals 8m

Building Your First Model

Lesson 1: Deep Dive into Gradient Descent 18m

Lesson 2: Classification Fundamentals 25m

Lesson 3: Neurons Explained 15m

Training & Evaluation

Lesson 1: Practical Gradient Descent 20m

Lesson 2: Deep Dive into Feature Engineering 21m

Lesson 3: Feature Engineering Explained 8m

Lesson 4: Deep Dive into Overfitting 11m

Lesson 5: Working with Tensors 23m

Lesson 6: Deep Dive into Feature Engineering 22m

Advanced Algorithms

Lesson 1: Advanced Tensors Techniques 17m

Lesson 2: Building Gradient Descent 21m

Lesson 3: Tensors Best Practices 17m

Lesson 4: Mastering Neurons 20m

Lesson 5: Working with Overfitting 22m

Lesson 6: Building Tensors 24m

Neural Networks

Lesson 1: Hands-On Gradient Descent 8m

Lesson 2: Advanced Tensors Techniques 14m

Lesson 3: Practical Classification 21m

Lesson 4: Working with Overfitting 18m

Model Deployment

Lesson 1: Deep Dive into Tensors 22m

Lesson 2: Mastering Tensors 17m

Lesson 3: Advanced Classification Techniques 10m

Lesson 4: Gradient Descent Best Practices 23m

Lesson 5: Practical Feature Engineering 12m

Real-World Applications

Lesson 1: Introduction to Classification 24m

Lesson 2: Understanding Gradient Descent 19m

Lesson 3: Introduction to Gradient Descent 23m