Next Selection Review on 23rd Feb 2025

Start building AI solutions with

Certification Programme in Generative AI Foundations and Applications

A hands-on

Generative AI course designed for working professionals


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Generative AI is Redefining
Human Potential and Innovation

  • "Generative AI to become a
    $1.3 trillion market by 2032." 1
  • "40% of organizations are already investing in Generative AI teams and budgets." 2

Trending Career Opportunities in
Generative AI

  • Software Engineer - Gen AI
  • AI Prompt Engineer
  • Lead ML Engineer
  • ML Engineer - LLMs & Gen AI
  • Gen AI Researcher
  • AI Architect
  • Senior ML Engineer
  • Generative AI Consultant
  • Lead Engineer - Gen AI
  • Senior NLP Engineer
  • Gen AI Architect
  • and More..

Experience the TalentSprint Edge

Global DeepTech Company powered by AI

  • Delivering cutting-edge learning experiences with AI at the core.
  • Leveraging AI to redefine executive education.

15 years of DeepTech Education

  • Diverse learning options from bootcamps to advanced eDegrees.
  • Futuristic programs offered in AIML, DataScience, Cybersecurity, Semicons, etc.

Top-tier
Partnerships

  • 60+ programs offered with top academic institutions like IITs, IIITs and IIMs.
  • Programs offered with global corporations like Google, Pegasystems, etc.

Distinctive Pedagogy for Learner Success

  • A learner-centric approach to deliver outcomes and satisfaction.
  • Hands-on, application-oriented learning through real-world case studies.

Next Selection Review on 23rd Feb 2025

+91-7075767163

Who is this Programme Best
Suited for?

This programme is for you if you are a

  • AI/Data Science practitioner seeking to build expertise in Generative AI
  • Tech professional aspiring to upgrade to Generative AI roles
  • Tech leader looking forward to adopting Generative AI in their workflow

Eligibility Criteria

  • Work Experience: Minimum 1 Year
  • Coding Experience: Programming knowledge required, ideally in Python

Generative AI Course Curriculum

This module introduces the fundamentals of Generative AI and builds a strong foundation in data processing across multiple modalities.

  • What is data: Sources & types
  • Data Insights & Applications: explain types of insights & areas of applications like what do you call an insight as? How do you generate it? How do you use it?
  • Automation, ML, DL & AI: terminology
  • Industrial use cases

This module focuses on building and understanding the key architectures and models that power Generative AI systems.

  • Types of ML problems: supervised, unsupervised, RL
  • Discriminative vs Generative
  • Evaluation metrics & Business implications
  • AI project life cycle

  • Introduction to ANN & DL
  • CNN for vision
  • Recurrent architectures for NLP
  • Advance NLP & transformers

  • What are Large Language Models (LLMs)?
  • Key architecture of LLMs: Transformer models
    1. Examples of LLMs: GPT, BERT, T5, and their advancements
  • LLM Training and data
    1. Training methodology: unsupervised learning
    2. Pretraining on large-scale datasets and transfer learning
  • Applications of LLMs
    1. Text generation, summarization, translation, and question-answering

This module explores advanced applications of Generative AI, including retrieval-augmented systems and autonomous agents.

  • Proprietary Models
  • Open-source Models
  • How to select the right model?
  • Model Sources

  • Prompt Engineering
  • The Need for Fine-Tuning
    1. The limitations of general-purpose LLMs
    2. Benefits of fine-tuning on domain-specific tasks (e.g., medical, legal, or technical content)
  • Fine-Tuning Methods
    1. Multi-task finetuning
    2. PEFT

  • Automating the deployment and scaling of LLM-based systems
    1. Monitoring performance, resource usage, and user feedback
    2. Continuous training, model versioning, and A/B testing
  • Model optimization and Deployment
    1. Quantization
    2. Pruning
    3. Model distillation

  • Prompt templates and variations
  • Simple Chatbot Implementation
    1. Creating a basic conversational agent
    2. Handling context and memory
    3. Implementing basic conversational flows
  • Conversational Memory Strategies
    1. Buffer memory
    2. Entity memory
    3. Conversation summary memory
  • Context Management
    1. Maintaining conversational context
    2. Implementing sliding window techniques
    3. Error Handling and Fallback Mechanisms

  • What is Retrieval-Augmented Generation (RAG)?
    1. Combining retrieval techniques with generative models for more accurate and relevant responses
    2. The architecture of RAG: Integrating search and generation steps
  • How RAG Works
    1. Retrieving context from external knowledge bases and incorporating it into generative tasks
    2. Use cases: Question answering, knowledge-driven content generation, and dialogue systems
  • Challenges in RAG
    1. Dealing with noisy data from retrieval sources
    2. Improving relevance and diversity in generated content

  • What is an AI Agent?
    1. Introduction to LangChain Agents
    2. Agent Components
    3. Practical Setup
  • Building Basic Agents
    1. Agent Architecture Design
    2. Hands-on Lab: Simple Agent Implementation
    3. Advanced Prompt Techniques
  • Multi-Agent Systems with LangChain
    1. Agent Collaboration Patterns
    2. Agent Team Architecture
    3. Hands-on Project

  • Exploring generative capabilities beyond text (e.g., image, video, music)
  • GAN
  • Diffusion models
  • LAMs, Knowledge graphs, VLMs

  • Ethical Implications of Generative AI
    1. Bias and fairness in generative models: Addressing biased training data
    2. Ethical concerns around deep fakes, misinformation, and privacy violations
    3. Intellectual property and copyright issues in generative content
  • Risks in Generative AI
    1. Model vulnerabilities: adversarial attacks, data poisoning, and model exploitation
    2. Impact on labour markets and the potential for job displacement
  • Compliance and Governance
    1. Regulations around AI, such as GDPR and AI Act
    2. Frameworks for responsible AI development
    3. Strategies for ensuring transparency and accountability in generative models

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Master the Essential Techniques of Generative AI

  • Multimodal Data
    Processing
  • Transformer
    Architectures
  • Attention
    Mechanisms
  • Fine-Tuning
    LLMs
  • Evaluation
    Metrics
  • Prompt
    Engineering
  • RAG
    Systems
  • AI Agent
    Design
  • LLMOps

Tools Covered

ts-gen-ai-tools

Who will be Your Programme Mentors?

Dr. Kishore Reddy
Konda

Expertise: Machine Learning, Computer Vision, Natural Language Processing (NLP), AI for Customer Support, Data Quality Management (DQM)

Kishore Reddy Konda is an accomplished AI researcher and machine learning expert with deep expertise in both theoretical and applied AI...

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Dr. Mohammed Habeebvulla

Expertise: Generative AI, Machine Learning, AI Architecture

Dr. Mohammed Habeebvulla is a Principal AI Engineer with expertise in developing AI solutions, including Generative AI and Large Language Models (LLM), for diverse industries...

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Bharath Narla

Expertise: Generative AI, Data Science, Machine Learning

Bharath Narla is an expert data science consultant and AI specialist with a strong track record of delivering transformative solutions across diverse industries...

Read More

How is this Programme Delivered? Experience high-impact immersive learning through

  • 100% live interactive sessions by expert faculty
  • 17 weeks part-time schedule with weekend-only classes Weekly lectures on Saturdays (Theory & concepts)
  • Hands-on learning through case studies and group projects Weekly lab on Sundays (Hands-on practice)
    Monthly industry case study session
  • Capstone project to solve real-world challenges with applied skills

Delivered on TalentSprint’s iPearl.ai Award-winning AI-powered platform

iPearl.ai is TalentSprint's cutting-edge digital learning platform, designed for experiential and remote learning. Built on Open edX, it seamlessly integrates live projects, peer-driven learning, cloud labs, video indexing, and more, all through a single sign-on. Delivering a unified, engaging experience for students and instructors alike, iPearl.ai ensures maximum outcomes and satisfaction.

  • Interactive
    Online Classes
  • AI-powered
    Video Archives
  • Personalized
    Learning Plans
  • Online
    Practice Labs
  • Group Activities
    and Team Work
  • One-to-One
    Mentor Support
  • Multi-device
    Access
  • Interactive
    Forums
  • And
    more...

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What are the Programme Outcomes?

Upon completion of this programme, you will be able to:

  • Master core principles and advanced applications
    of Generative AI.
  • Adopt best practices in prompt engineering and
    model fine-tuning.
  • Design and deploy scalable, production-ready
    GenAI solutions.
  • Drive AI innovation by leading teams and implementing
    GenAI systems across industries.
  • Transition into high-demand AI roles with specialized,
    industry-relevant skills.

What is the Enrollment Process for this Programme?

It is a simple 3-step process

  • Apply for
    the programme
  • Await
    selection
  • Join the
    programme

Generative AI Course Fee

Without Scholarship₹1,20,000 With Scholarship ₹96,000
Registration Fee: ₹20,000 Registration Fee: ₹20,000
Balance Fee: ₹1,00,000 Balance Fee: ₹76,000
(*18% GST extra as applicable)

Application fee₹2,000

Modes of payment available


  • Internet Banking

  • Credit/Debit Card

  • UPI Payments

Easy Financing Options

Interest-Based Schemes

EMI as low as ₹5,084/Month

EMI Options

Check my eligibility for the scholarship

Special Pricing for Corporates

*Applicable only for enterprises nominating their employees as a group
Fees paid are non-refundable and non-transferable.

Loan Partners

Frequently Asked Questions

Generative AI, a paradigm shift in the world of AI, goes beyond analysing data to create entirely new, realistic datasets, paving the way for a new era of exploration and efficiency. The Gen AI market is set to reach $200 billion by 2032, making up 20% of total AI spending. By 2025, over 10% of all data will be AI-generated, leading to seamless human-AI collaboration.

Generative AI is now being used across industries to:

  • Boost Efficiency: Automates repetitive tasks allowing human capital for strategic thinking and innovation.
  • Enhance Customer Experience: Delivers personalized experiences at scale through tailored content and targeted marketing.
  • Fast-track Product Development: Accelerates R&D and optimizes product designs by identifying potential issues early.
  • Drive Innovation: Helps brainstorm new ideas and concepts, giving businesses a competitive edge.

To help professionals navigate and leverage the evolving frontier of AI, this one of a kind programme equips you with the expertise to lead in this transformative technological era.

Over the past 15 years, TalentSprint has been at the forefront of DeepTech education, delivering transformative learning experiences and offering programs that empower professionals to thrive in rapidly evolving industries.

  • AI-Powered Learning: TalentSprint delivers cutting-edge learning experiences with AI at the core and leverages AI to redefine executive education
  • Expert-led sessions: 100% live-interactive classes by expert faculty with flexible learning format
  • Hands-on Experience: Weekly lab sessions for practical learning, monthly industry case studies, and group projects
  • Master Generative AI techniques: Gain expertise in transformers, LLM fine-tuning, RAG systems, prompt engineering, and LLMOps

The programme brings a transformative learning experience, perfected for professionals.

  • Hands-On Learning: Focus on real-world case studies and application-oriented projects.
  • Career Advancement: Strengthen technical skills and enhance your professional profile with industry-relevant expertise.
  • Experiential Learning with iPearl.ai: Attend live sessions on TalentSprint’s award-winning AI-powered learning platform for an interactive and engaging experience.

If you're passionate about mastering Generative AI, this program is designed to help you level up your skills and expertise. It’s suitable for you if you are a:

  • AI/Data Science practitioner seeking to build expertise in Generative AI
  • Tech professional aspiring to upgrade to Generative AI roles
  • Tech leader looking forward to adopting Generative AI in their workflow

View All

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