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Generative AI Techniques

Online Live | 40 Hours | Basic Certification
₹23,482.00 (Inc. GST)

The dates for the upcoming class will be announced soon.

Faculty would be from the industry

Categories: AI & ML, Online Live Courses

To further the objectives of EICT Academy under the Ministry of Electronics & Information Technology (MeitY), E&ICT Academy, IIT Kanpur brings you various courses in Emerging Technologies, Computer Sciences, Entrepreneurship, Business and many more. This course is curated and delivered by Industry Experts equipped with a wealth of experience and an in-depth understanding of the subject matter.

Course Overview

Start Date : The dates for the upcoming class will be announced soon.
Course Type: Comprehensive 40-hour program
Duration: 2 Months
Total Lectures: N/A
Number of lectures for the above (if OLD): 20
Skill Level: Intermediate
Assessments: Hands-on Projects, Assignments, Final Assessment
Certificate: Yes

For Self-Paced Programs: 2 Doubt Session(s)/Master Classes

Objective / Outcome Expected:

Comprehensive understanding of generative AI techniques and their applications.
Proficiency in designing and implementing generative AI models for various tasks.
Practical experience through real-world projects and case studies.
Application of generative AI techniques to real-world problems.
Insight into reinforcement learning for generative tasks.
Awareness and consideration of ethical challenges in generative AI.

Target Audience:

Ideal for individuals with a solid understanding of basic programming and machine learning concepts.
Suitable for data scientists, AI engineers, researchers, and professionals who want to specialize in generative AI.
Also beneficial for those interested in exploring advanced applications and cutting-edge trends in generative AI.

Key Features:

Comprehensive coverage of generative AI techniques and applications.
Practical experience through hands-on projects and real-world case studies.
Certification upon successful completion.

Faculty Members

S. Aggarwal
Nandan Mishra
Niraj T.
Shantam D.
U. Tiwari
S. Garg

Delivery Mode & Duration

Online Live Mode- 2 Months (40 Hours Online Live sessions + 60 Hours of Assignment and Hands on)

Prerequisites

Solid understanding of basic programming and machine learning concepts.
Recommended prior knowledge in AI technologies.
Suitable for data scientists, AI engineers, researchers, and professionals looking to specialize in generative AI.
Familiarity with mathematics is beneficial but not mandatory.

Curriculum

Module 1: Introduction to Generative AI

Overview of generative AI and its applications
Introduction to generative models
Key concepts: generative models vs. discriminative models, probability distributions

Module 2: Fundamentals of Deep Learning

Introduction to deep learning and neural networks
Training neural networks: backpropagation, optimization algorithms
Regularization techniques: dropout, L1/L2 regularization
Convolutional Neural Networks (CNNs) for generative tasks

Module 3: Variational Autoencoders (VAEs)

Introduction to autoencoders
Understanding VAEs: encoder, decoder, and latent space
Variational inference and the reparameterization trick
Applications of VAEs: image generation, data compression

Module 4: Generative Adversarial Networks (GANs)

Introduction to GANs and their components (generator, discriminator)
GAN training process: minimax game, adversarial loss
Architectural variations: DCGAN, WGAN, CGAN, etc.
GAN applications: image synthesis, style transfer

Module 5: Sequence Generation with Recurrent Neural Networks (RNNs) (6 hours)

Introduction to RNNs and their variants (LSTM, GRU)
Applications of RNNs for sequence generation: text generation, music generation
Training techniques for sequence generation models
Attention mechanisms for improving sequence generation

Module 6: Reinforcement Learning for Generative Tasks

Introduction to reinforcement learning (RL)
RL basics: Markov Decision Process (MDP), policy gradients
RL for generative tasks: policy-based methods, generative adversarial imitation learning
Applications of RL for generative AI: game playing, robotics

Module 7: Advanced Topics and Applications

Deep generative models: PixelCNN, Glow, RealNVP
Adversarial examples and defenses
Domain adaptation and transfer learning in generative AI
Ethical considerations and challenges in generative AI

Module 8: Hands-on Projects and Case Studies

Practical implementation of generative AI models using popular frameworks (e.g., TensorFlow, Py Torch)
Guided projects and assignments to reinforce concepts learned
Case studies showcasing real-world applications of generative AI

Module 9: Future Trends and Conclusion

Emerging trends in generative AI research
Challenges and opportunities in the field
Final thoughts and wrap-up of the course

FAQs

Section 1: Generative AI Techniques and Applications Course Overview

Question 1: What is the Generative AI Techniques and Applications Course?

Answer 1: The Generative AI Techniques and Applications Course is an extensive 40-hour program designed to provide participants with a comprehensive understanding of generative AI techniques and their real-world applications.

This course offers 100% LIVE online delivery, making it accessible to a wide range of learners.

Question 2: What should I expect from the Generative AI Techniques and Applications Course?

Answer 2: Expect to gain a deep understanding of various generative AI techniques and how to apply them to practical problems. This course covers topics such as Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), sequence generation with Recurrent Neural Networks (RNNs), reinforcement learning for generative tasks, and more. You’ll also work on hands-on projects and case studies.

Question 3: What should I NOT expect from the Generative AI Techniques and Applications Course?

Answer 3: This course is not designed for complete beginners. It assumes a solid understanding of basic programming and machine learning concepts. If you’re new to AI and machine learning, you might find this course challenging.

Question 4: Which topics/modules are covered in the Generative AI Techniques and Applications Course?

Answer 4: The course curriculum includes modules on Generative AI introduction, fundamentals of deep learning, Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), sequence generation with RNNs, reinforcement learning for generative tasks, advanced topics, hands-on projects, and future trends.

Question 5: What type of learning experience should I expect from the Generative AI Techniques and Applications Course?

Answer 5: This course offers 100% LIVE Online delivery for doubt sessions and master classes. The learning experience is interactive and enriched by lectures from experienced instructors. Real-time interaction and question resolution are integral to the course.

Question 6: Is a certification granted upon completing the Generative AI Techniques and Applications Course?

Answer 6: Yes, upon successful completion of the program, you will receive a certification from the prestigious IIT Kanpur. This certification is recognized in the industry and is secured using blockchain technology.

Question 7: When does the course start, and how long does it take to complete?

Answer 7: The course’s duration and start date may vary based on the specific program you choose. For precise information on course schedules, we recommend referring to the official website.

Section 2: Training Pedagogy for Generative AI Techniques and Applications Course

Question 1: How will the course be delivered?

Answer 1: The complete course will be delivered 100% ONLINE LIVE through dependable online meeting tools. Only class recordings will be shared with you for revision or when you miss any class.

Question 2: What happens if I miss a session or class?

Answer 2: We understand that life can get a bit busy sometimes. If you miss a class due to urgent and unavoidable circumstances, we shall assist you with the recordings which will be available on the portal, you have enrolled for a program for your career enhancement, and our sincere advice would be to absent yourself from the class only in extreme, urgent, and unavoidable circumstances. It’s just a matter of few months when this course will be finished, and you embark on a bright career.

Question 3: How many assignments and projects will be there?

Answer 3: Each module will have 2 assignments. After completion of each module, there will be a minor project. By the completion of the training, every participant should undergo one month of capstone. Throughout the course, you’ll have a series of hands-on assignments that reinforce the concepts you learn. These assignments are designed to help you apply your knowledge practically and build a strong foundation in full stack development.

Question 4: Who will assist me if I have questions or doubts?

Answer 4: As it is a 100% ONLINE LIVE training with two-way communication, you can get your doubts resolved then and there.

Before the start of every class, the faculty will be available for 10 to 15 minutes to clear your doubts.

Apart from this, we have weekly two-hour doubt sessions, where you can ask doubts one-to-one. We foster a supportive learning environment. Our experienced instructors and dedicated support team are available to address any doubts or questions you may have during the course. You can reach out through our communication channels for timely assistance.

Question 5: What do I need for the training?

Answer 5: To make the most of the training, you’ll need a computer or laptop with a stable internet connection. You’ll also need code editing software, which we will guide you on setting up. A curious mind and enthusiasm to learn are the key ingredients for success!

Question 6: What are the prerequisites for this course?

Answer 6: To succeed in this course, you should have a solid understanding of basic programming and machine learning concepts. While prior knowledge in AI technologies is recommended, it’s not mandatory. Familiarity with mathematics is beneficial but not required.

Question 7: Will we get value add sessions?

Answer 7: Absolutely, we believe in providing holistic learning. Apart from the core curriculum, there will be master trainers and industry experts who will deliver value-added sessions, workshops, and seminars to enhance your soft skills, communication abilities, and industry insights.

Question 8. Who all will be our instructors?

Answer 8: Our instructors are experienced industry professionals with a deep understanding of full stack web development. They bring practical insights and real-world examples to the classroom, ensuring an engaging and valuable learning experience.

Section 3: Time Commitment for Generative AI Techniques and Application (40 hours) Course

Question 1: What is the time commitment expected for the program?

Answer 1: To successfully graduate from the Course, we recommend dedicating at least 12-15 hours per week. This commitment ensures that you can effectively engage with the course material, complete assignments, and gain a comprehensive understanding of the concepts. While the curriculum is robust, we have designed the course with the needs of working professionals in mind, making it manageable and accommodating.

Question 2: Will the course require different time commitments for different modules or topics?

Answer 2: While the time commitment may vary slightly depending on the complexity of the modules or topics, maintaining a consistent amount of study time each week is advisable for comprehensive understanding.

Section 4: Career Prospects and Support for Generative AI Career

Question 1: What are the career prospects after completing the Generative AI Techniques and Applications Course?

Answer 1: After completing this course, you’ll be well-prepared for various career opportunities in generative AI. You can apply your expertise in roles related to image generation, text generation, game playing, robotics, and more.

Question 2: How will my doubts/questions be addressed in an online program?

Answer 2: In the Data Analyst Course, you have access to a dedicated peer-to-peer discussion forum. Here, you can post your queries, and your peers, faculty members, and teaching assistants will provide answers within a day. Regular Q&A sessions with faculty members are conducted to clarify any conceptual doubts. This dynamic learning environment ensures that your questions are addressed promptly and comprehensively.

Question 3: Will I receive special career services or support?

Answer 3: As you embark on your Generative AI journey, you can trust that the course is designed to provide holistic support, ensure effective doubt resolution, and equip you with the resources needed for a successful career in the field of data analytics.

Section 5: Course Fees, Refund Policy, and Financials

Question 1: What is the fee for the program?

Answer 1: The fee for the Data Analyst Course is INR 19,900 excluding GST plus applicable taxes.

Question 2: How can I make payments for the program?

Answer 2: All training fees must be paid to the designated IFACET – IITK account. Payments should not be made to any other entity or individual.

Question 3: Can I pay program fees in EMIs? If not, can you assist me in securing one?

Answer 3: Yes, you have the option to convert the program fees into a no-cost EMI (Equated Monthly Installment) plan with your credit card. This allows you to pay in convenient installments.

Question 4: Will I have to pay any extra amount for EMI transactions?

Answer 4: Choosing the 0% credit card EMI option typically means that processing fees or down payments are not charged. However, please note that your bank may apply GST or other taxes on the interest component of the EMI. You should check with your bank for specific details.

Question 5: What is the Refund Policy of the program?

Answer 5: Refund Policy:

Before the Start of the program

Refunds can be claimed for the paid amount towards the Program before the Program Start Date. This can be done by getting in touch with your academic counsellor.
Refund requests can also be initiated by reaching out to your Admissions Counsellor via email, providing reasons for withdrawal. A processing fee of 5% of the program will be deducted from the total amount paid.
It takes 3 to 4 weeks to refund the fees to your account from the date of acceptance of your refund request. The fees shall be refunded in the same account from which it was paid to us.
No refund requests will be entertained under any circumstances if raised after the Cohort Commencement Date.

After the commencement of the program:

The candidate is eligible for 90% refund of the program fees if he wishes to withdraw from the program within 15 days of the start of the program.
Such requests for refund shall be intimated to us over an email. There should always be a confirmation from our end that we have received your request.
It takes 3 to 4 weeks to refund the fees to your account from the date of acceptance of your refund request. The fees shall be refunded in the same account from which it was paid to us.
No refund requests will be entertained under any circumstances if raised after 15 days of the start date of the program.

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