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Course Highlights

Applied Generative AI and Agentic AI Program Highlights

4.5-month Executive-Friendly Format: Designed for freshers, tech professionals and leaders, this programme fits seamlessly fits into everyone's busy schedule

Industry-ready Curriculum: Master foundational concepts, explore advanced architectures, and implement practical solutions using Generative AI

Hands-on Learning: Dive into real-world case studies, lab sessions, and mini-projects to build expertise in Generative AI tools and techniques

Capstone Project: Design and deploy a complete Generative AI application with advanced techniques like RAG and multi-modal models

Career Support:

  • Freshers get exclusive access to monthly placement drives
  • Working professionals benefit from TalentSprint’s Career Accelerator, inclusive of expert sessions, profile building, job alerts, and a powerful alumni network
  • Skill Type

  • Course Duration

  • Domain

  • GOI Incentive applicable

  • Course Category

  • Nasscom Assessment

  • Placement Assistance

  • Certificate Earned

  • Badge Earned

  • Content Alignment Type

  • NOS Details

  • Mode of Delivery

Course Details

Learning Objectives

What will you learn in the Certification Program in Applied Generative AI and Agentic AI Course?

A comprehensive and hands-on certification programme designed to equip learners with in-demand niche skills in Python, Machine Learning, Deep Learning, Generative AI, Agentic AI, LLMs, and AI Algorithms, while enabling them to gain proficiency in 10+ industry-relevant tools.

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Reasons to enrol

Why should you take the Certification Program in Applied Generative AI and Agentic AI Course?

  • Master Core GenAI Skills: Understand the foundations of Generative AI and its real-world applications
  • Hands-on Learning: Apply your knowledge through lab sessions, mini-projects, and case studies
  • Advanced Techniques: Build expertise in RAG systems, LLMOps, Prompt Engineering, and more
  • Learn from Industry Experts: Gain insights from expert faculty with deep expertise in AI and real-world applications
  • Explore High-demand Opportunities: Transition into AI roles with specialized, industry-relevant skills
  • This 4.5-month executive-friendly program is designed to help working professionals become AI leaders
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Ideal Participants

Who should take the Certification Program in Applied Generative AI and Agentic AI Course?

This Generative AI and Agentic AI course is for:

  • A working professional looking to stay ahead by leveraging Generative AI for smarter decision-making and career growth.
  • A fresher or career starter eager to build in-demand AI skills and unlock high-growth opportunities.

Eligibility Criteria

Education: Bachelor’s degree with a minimum 50% academic percentage. Coding experience is not required.

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Curriculum

Curriculum

Bridge Sessions

  • Module 1: Foundations of Generative AI
  • Module 2: Architectures and Models in Generative AI
  • Module 3: Advanced Prompt Engineering and RAG
  • Module 4: Agentic AI
  • Module 5: Practical Implementation of Generative AI
  • Module 6: Building, Hosting, and Operationalizing GenAI Applications
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skills and tools

Tools you will learn in the Certification Program in Applied Generative AI and Agentic AI Course

You will learn a variety of in-demand skills, including:

Programming Languages: Python

Tools and Libraries:

  • Machine Learning: Scikit-learn, TensorFlow, PyTorch
  • Deep Learning: Keras, Hugging Face, OpenAI API
  • Data Manipulation: Pandas, AWS PartyRock
  • Natural Language Processing (NLP): Hugging Face Transformers, NLTK, spaCy
  • Computer Vision: OpenCV, TensorFlow, n8n tools
  • Speech Processing: Speech Recognition, Text-to-Speech (TTS) Libraries
  • Multimodal Frameworks: LangChain, Vector Databases

Technologies

  • Data Modalities: Text, Image, Audio, Video
  • Machine Learning and AI Algorithms
  • Deep Learning Frameworks: Transformers, Attention Mechanisms, and Multimodal Integration
  • Large Language Models (LLMs): Fine-Tuning, Evaluation Metrics, and Deployment Best Practices
  • AI Agents: Autonomous Action Agents, RAG Systems, Platform Integration
  • Operational Practices: LLMOps, Security, and Performance Monitoring
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