Programme Content
in Just 7-8 Months
How You Go From Learning to Orchestrating
Module 1: Foundations of AI, ML, and Generative AI
Learners build a strong foundation in AI, ML, and Generative AI. This module helps them understand how data is prepared, explored, and used to build AI systems, setting the base for the advanced modules in the program.
Module 2: Deep Dive into Machine Learning Algorithms
Learners explore key machine learning algorithms used for prediction, classification, clustering, and decision-making. This module helps them understand how to train, evaluate, and improve ML models for real-world use cases.
Module 3: Understanding Deep Learning
Learners understand how deep learning models solve complex problems involving images, patterns, and sequential data. The module gives them practical exposure to building neural network-based AI solutions.
Module 4: Exploring NLP
Learners understand how deep learning models solve complex problems involving images, patterns, and sequential data. The module gives them practical exposure to building neural network-based AI solutions.
Module 5: Exploring Cloud Ecosystems
Learners understand how deep learning models solve complex problems involving images, patterns, and sequential data. The module gives them practical exposure to building neural network-based AI solutions.
Module 6: Advancement in Hypervisors
Learners explore how virtualization powers cloud infrastructure. This module helps them understand hypervisors, virtual machines, and migration concepts used in modern cloud and enterprise environments.
Module 7: Engaging with Generative AI
Learners understand how Generative AI systems create content and support business use cases. This module introduces major generative model types and shows how they can be applied in real-world AI applications.
Module 8: Understanding LLMs
Learners explore how Large Language Models work and how they are used to build intelligent applications. This module helps them connect LLM concepts with practical tools used in enterprise GenAI solutions.
Module 9: GenAI Application Development Prompting Techniques
Learners develop the skills needed to interact with and build applications using Generative AI models. This module helps them design better prompts, evaluate outputs, and create practical GenAI workflows.
Module 10: AI Embeddings & Retrieval
Learners understand how AI systems retrieve and use relevant information. This module prepares them to build RAG-based LLM applications that can connect with knowledge bases and deliver contextual responses.
Module 11: Understanding Agentic AI
Learners explore how AI agents can reason, plan, and complete tasks with minimal human input. This module helps them understand how agentic workflows can be used to automate real business processes.
Module 12: Container Orchestration
Learners understand how AI and LLM applications are packaged, deployed, and managed using containers. This module prepares them to deploy scalable and production-ready AI applications using Docker and Kubernetes.
Module 13: AI ML on Cloud and Cloud Security
Learners understand how to secure cloud-based AI environments. This module helps them learn the security, governance, and resilience practices required to protect AI systems, data, and cloud infrastructure.
Module 14: AIOps with AWS
Learners understand how cloud platforms support Gen AI and LLM workloads at scale. This module helps them learn how to deploy, manage, optimize, and monitor AI applications using cloud services.
