Modern Computer Vision & Generative AI with Machine Learning Online Course
Modern Computer Vision & Generative AI with Machine Learning Online Course
The Modern Computer Vision & Generative AI with Machine Learning Online course has been designed and tailored to provide a blend of foundational knowledge and advanced skills, this course is your stepping stone to mastering the art and science of image analysis, object detection, and generative AI. Through hands-on projects and real-world scenarios, you will gain proficiency in using cutting-edge tools like Stable Diffusion, KerasCV, TensorFlow, PyTorch, and JAX to build and deploy AI solutions effectively.
Key Learning
- Comprehensive understanding of computer vision and generative AI techniques.
- Hands-on experience with pre-trained models, custom datasets, and real-world applications.
- Advanced insights into Stable Diffusion and generative art creation.
- Skill development in leveraging Python-based frameworks for AI projects.
Who should take this Course?
This course is perfect for beginners with a fundamental grasp of Python programming and machine learning, as well as advanced learners looking to expand their expertise in computer vision and AI. It caters to professionals, students, and enthusiasts eager to explore practical applications and creative possibilities in AI.
Course Outline
The Modern Computer Vision & Generative AI with Machine Learning Online Course covers the following topics -
Module 1: Welcome and Introduction
- Overview and Course Outline
- Tips for Success in This Course
- Accessing Course Code and Materials
Module 2: Image Classification with Fine-Tuning and Transfer Learning
- Understanding Pre-trained Image Classifiers
- Implementing Pre-trained Models in Python
- Exploring Transfer Learning and Fine-Tuning
- Building Custom Classification Solutions
- Engaging Exercises for Practical Learning
Module 3: Object Detection Techniques
- Fundamentals of Object Detection
- Key Metrics: IoU, Non-Max Suppression, and Confidence Scores
- Using Pre-trained Models for Object Detection
- Dataset Formats: COCO and Pascal VOC
- Hands-On with LabelImg for Data Annotation
- Fine-Tuning Object Detection Models with Custom Data
- Practical Object Detection Exercises
Module 4: Generative AI with Stable Diffusion
- Exploring Stable Diffusion for Generative Art
- How Diffusion Models Work (Optional Deep Dive)
- Understanding Diffusion Architecture – Unet
- Prompt Conditioning and Image Generation
- Navigating Diffusion Model Source Code (Optional)
Module 5: Setting Up Your Environment
- Step-by-Step Guide to Setting Up Anaconda
- Installing Essential Libraries for AI Development
Module 6: Python Coding Essentials for Beginners
- Coding Tips for Efficient Learning
- Building Foundational Skills Through Guided Exercises
- Insights into Using Jupyter Notebooks Effectively
Module 7: Advanced Learning Strategies for Machine Learning
- Structuring Your Learning Path for Maximum Retention
- Guidance on Sequencing-Related Courses
Skills Acquired
- Proficiency in KerasCV for deep learning applications.
- Expertise in image classification and transfer learning.
- Ability to create and manage custom datasets for object detection.
- Skills to implement generative AI techniques using Stable Diffusion.
- Mastery of deep learning frameworks like TensorFlow, PyTorch, and JAX.
Why Choose this Course?
- Comprehensive Curriculum: Covers the entire spectrum of computer vision and generative AI, from foundational to advanced topics.
- Practical Focus: Gain hands-on experience with industry-standard tools and real-world exercises.
- Flexible Learning: Learn at your own pace with lifetime access to updated course materials.
- Expert Guidance: Benefit from a structured approach designed by AI and machine learning professionals.
