Covers foundational skills in Python programming, data handling with NumPy and Pandas, data analysis visualization, statistical foundations, machine learning lifecycle, and model evaluation optimization.
Module 2: NLP & Deep Learning
Includes natural language processing fundamentals, neural networks, deep learning concepts, computer vision techniques, sequence and time-series modeling, plus model training and performance optimization.
Module 3: Generative AI & Agentic Orchestration
Focuses on generative AI foundations, prompt engineering techniques, large language model applications, retrieval-augmented generation (RAG) systems, autonomous agentic AI workflows, and monitoring evaluation of AI agents.
Module 4: MLOps & Production Deployment
Encompasses model deployment strategies, MLOps lifecycle automation, CI/CD for machine learning systems, model monitoring performance tracking, and production-ready AI infrastructure.
Additional Program Features
- *Hands-on Projects*: 35 projects across modules, including sales forecasting, sentiment analysis, text-to-image generation, Docker deployment, and multi-agent collaboration.
- *Enterprise Capstone Project*: End-to-end AI solution integrating ML, NLP, generative AI, and deployment for real-world problems like fraud detection or recommendation systems.
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- *Labs & Datasets*: Real-time datasets from Kaggle, UCI, AWS; labs with TensorFlow, PyTorch, LangChain, Docker in cloud environments.
• Data Science with Python Certification Course
• Data Analyst Masters Course
• Data Visualization with Tableau Using AI
