The AI for Developer Training Online is designed to provide comprehensive, in-depth training in AI for Developer 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 Fundamentals of Artificial Intelligence and Machine Learning Data Preprocessing and Exploration Techniques Building and Training Machine Learning Models Deep Learning Concepts and Neural Networks Natural Language Processing (NLP) Basics Computer Vision Techniques Model Evaluation and Hyperparameter Tuning Deployment of AI Models in Real-World Applications Using AI Frameworks and Libraries (TensorFlow, PyTorch, etc.) 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) The program covers foundational concepts through to advanced techniques to ensure you gain job-ready expertise.
