AI for Developer Course Online Training

Prerequisites

• Basic Programming Knowledge (Python, Java, or similar)
• Understanding of Data Structures and Algorithms
• Familiarity with Mathematics (Linear Algebra, Probability, Statistics)
• Basic Knowledge of Machine Learning Concepts
• Experience with Linux/Unix Command Line
• Understanding of Software Development Life Cycle (SDLC)
• Knowledge of Cloud Platforms

What Will You Learn in this Training

1. Fundamentals of Artificial Intelligence and Machine Learning
2. Data Preprocessing and Exploration Techniques
3. Building and Training Machine Learning Models
4. Deep Learning Concepts and Neural Networks
5. Natural Language Processing (NLP) Basics
6. Computer Vision Techniques
7. Model Evaluation and Hyperparameter Tuning
8. Deployment of AI Models in Real-World Applications
9. Using AI Frameworks and Libraries (TensorFlow, PyTorch, etc.)
10. Ethical Considerations and Best Practices in AI Development

What’s New in AI for Developers (2026)

• AI copilots embedded in IDEs and development workflows
• Autonomous AI agents for task planning and execution
• Multimodal AI models (text, code, image, audio)
• Long-context models supporting full codebases
• AI-first APIs with tool calling and agent frameworks
• Natural language to code, tests, and deployments
• On-device and private AI models
• Built-in AI security, governance, and compliance

Tools Covered

• OpenAI API (GPT models, embeddings, assistants)
• ChatGPT and Prompt Engineering Tools
• Python for AI Development
• Jupyter Notebook
• TensorFlow
• PyTorch
• LangChain
• Hugging Face Transformers
• Vector Databases (FAISS / Pinecone – concepts and usage)
• REST APIs for AI Integration
• Git and GitHub
• Cloud Platforms (AWS, Azure, Google Cloud – AI services overview)