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AI Catalyst™ Associate Program (AI-CAP)
A Comprehensive
3 - Months AI Training,
Project & Internship Program
A Comprehensive
3 - Months AI Training, Project
& Internship Program
About AI-CAP
The AI Catalyst™ Associate Program (AI-CAP) is a hands-on, project-based training and internship program aimed at empowering technical students to gain real-world AI skill set experience. Designed for those passionate about AI, this internship will fulfill your institution’s academic requirements and additionally give you personalized career mentorship.
Why Join AI-CAP?
Personalized Attention
With limited seats only 25 participants per Trainer, the program ensures personalized support and meticulous hands-on experience
Expert Mentorship
One-on-one sessions with industry veterans who bring over 20-40 years of experience in AI, technology, and leadership
Hands-On Projects
Gain practical experience by working on a group project and an individual project—applying AI to real-world problems
Exclusive Certification
Earn a course completion certificate and a letter of internship to enhance your resume
Key Program Highlights
Foundation Course: Immersive learning that covers the basics of AI, making advanced concepts approachable
Intermediate Course: Deeper learning that introduces advanced AI tools and real-world applications
Group Project: Collaborate on a practical AI project with guidance from experienced mentors. Focus areas include industry-relevant AI applications
Independent Project: Showcase your individual capabilities with an independent project aligned with your interests or career goals
Experience 1×1 mentorship with seasoned professionals who will guide you through career paths and AI skills development
Students have the option to attend 2x In-person sessions at our office during the internship. These workshops will include practical exercises, networking events, and industry engagement opportunities.
Meet Our Mentors
Kallol Hazra
Sr. Consultant & Mentor, QCP
Expertise: Solution Selling, Talent Transformation With 35+ years in tech sales and workforce development, Kallol’s mentorship focuses on improving not only technical expertise but also the soft skills necessary for thriving in AI roles.
Praveen Kumar
Director - QCP
Expertise: GTM solutions, Workforce Transformation | With over 20 years of experience in product lifecycle management and business development, Praveen is a strategic advisor for career paths in AI and technology.
Ramaprasad Srinivasan
Sr. Consultant & Mentor, QCP
Expertise: Computer Technology, AI Integration A leader with over 30 years at Intel, Ramaprasad offers deep insights into AI platforms and digital transformation strategies, helping students align their projects with industry needs.
Program Team
Sinchana
Program Co-ordinator
Limited Seats Available
With only 75 spots open, our program ensures parallel 3x batches of 25 students each, for personalized attention and interactive learning. Enroll now to secure your spot and be part of an exclusive cohort.
What You Get
Meet Our Trainers
Dushyant Singh
Trainer
Training and Product Lead
Vinodhini Manoharan
Co-trainer
Product Development Trainer
Praveen Kumar
Co-trainer
Director & Founder
Course Curriculum
Estimated Duration: 12 week(s)
1. Introduction to AI 6 lesson(s)
- Live Session : Introduction to AI Live lesson
- Understanding AI
- Evolution of AI
- Significance of AI in the Modern World
- Applications of AI
- Introduction to AI (Recording)
2. Introduction to Machine Learning 5 lesson(s)
- Introduction to Machine Learning Live lesson
- Introduction to Ml
- Types of ML
- Big Data
- Introduction to Machine Learning (Recording)
3. Intoduction to Deep Learning and Neural Networks 5 lesson(s)
- Intoduction to Deep Learning and Neural Networks Live lesson
- Introduction to Neural Network
- Introduction to Deep Learning
- Applications Of Deep Learning
- Introduction to Deep Learning (Recording)
4. AI Tools and Platforms 4 lesson(s)
- AI Tools and Platforms Live lesson
- Introduction to AI Development tools
- Cloud Based AI services
- AI Tools and Platforms (Recording)
5. Practical Applications and Future trends in AI 4 lesson(s)
- Practical Applications and Future trends in AI Live lesson
- Orange data mining tool
- Project
- Orange Data Mining (Recording)
6. AI Ethics, Biases, & Societal Impact 7 lesson(s)
- AI Ethics, Biases, & Societal Impact Live lesson
- Ethical Considerations in AI & Why it Matters
- Impact of AI
- Regulation and Governance
- Perspectives on AI Ethics
- Indian potential on AI level
- AI Ethics, Biases, & Societal Impact (Recording)
7. Introduction to Python 11 lesson(s)
- Introduction to Python Live lesson
- Programming Languages and its types, Introduction to Python
- Basics of Python syntax & Concept
- Python Beyond Basics: Advanced Programming Techniques
- Python Session - 2 Live lesson
- Python Session - 3 Live lesson
- Python Session - 4 Live lesson
- Python Session 1 - Recording
- Python Session 2 - Recording
- Python Session 3 - Recording
- Python Session 4 - Recording
8. Machine Learning Algorithms 5 lesson(s)
- Machine Learning Algorithms Live lesson
- Recap of Machine Learning
- Supervised Learning Algorithms
- Unsupervised Learning Algorithms
- Reinforcement Learning Algorithms
9. Deep Learning Algorithms 4 lesson(s)
- Introduction to Deep Learning Algorithms Live lesson
- Recap to Neural Network & Deep Learning.
- Deep Learning Algorithms
- Deep Learning v/s Machine Learning
10. Natural Language Processing (NLP) 5 lesson(s)
- Natural Language Processing (NLP) Live lesson
- Introduction to NLP and Its Key Benefits
- Applications and Evolution of NLP
- Concepts of NLP: From Data Cleaning to Word Embeddings
- Case Study and Working of ChatGPT in NLP Applications
11. Computer Vision and AI Applications 4 lesson(s)
- Introduction to Computer Vision and AI Applications Live lesson
- Introduction and History of Computer Vision
- Human Vision vs. Computer Vision and Applications of Computer Vision
- Key Concepts in Computer Vision
12. Internet Of Things (IOT) 4 lesson(s)
- Internet Of Things (IOT) Live lesson
- Introduction to IoT and Its History
- How IoT Works and Technologies Powering IoT
- IoT Applications, Benefits and Challenges, and Future Trends
13. AI and Robotics 4 lesson(s)
- AI and Robotics Live lesson
- Introduction to Robotics and AI Integration: History, Roles, Applications, Benefits, and Challenges
- Reinforcement Learning in Robotics
- Future Trends in AI and Robotics
14. Evaluation Metrics 3 lesson(s)
- Evaluation Metrics Live lesson
- Introduction to ML Model Evaluation and Its Significance
- Exploration of different evaluation metrics for assessing model performance.
15. Generative Adversarial Networks (GANs) and Autoencoders  5 lesson(s)
- Generative Adversarial Networks (GANs) and Autoencoders Live lesson
- What are Generative Adversarial Networks (GANs)?
- How GANs Work and Applications of GAN.
- Use cases of GAN.
- What are Autoencoders? And its Application
16. Final Assessment 1 lesson(s)
- Assessment
1. Introduction to AI 6 lesson(s)
- Live Session : Introduction to AI Live lesson
- Understanding AI
- Evolution of AI
- Significance of AI in the Modern World
- Applications of AI
- Introduction to AI (Recording)
2. Introduction to Machine Learning 5 lesson(s)
- Introduction to Machine Learning Live lesson
- Introduction to Ml
- Types of ML
- Big Data
- Introduction to Machine Learning (Recording)
3. Intoduction to Deep Learning and Neural Networks 5 lesson(s)
- Intoduction to Deep Learning and Neural Networks Live lesson
- Introduction to Neural Network
- Introduction to Deep Learning
- Applications Of Deep Learning
- Introduction to Deep Learning (Recording)
4. AI Tools and Platforms 4 lesson(s)
- AI Tools and Platforms Live lesson
- Introduction to AI Development tools
- Cloud Based AI services
- AI Tools and Platforms (Recording)
5. Practical Applications and Future trends in AI 4 lesson(s)
- Practical Applications and Future trends in AI Live lesson
- Orange data mining tool
- Project
- Orange Data Mining (Recording)
6. AI Ethics, Biases, & Societal Impact 7 lesson(s)
- AI Ethics, Biases, & Societal Impact Live lesson
- Ethical Considerations in AI & Why it Matters
- Impact of AI
- Regulation and Governance
- Perspectives on AI Ethics
- Indian potential on AI level
- AI Ethics, Biases, & Societal Impact (Recording)
7. Introduction to Python 11 lesson(s)
- Introduction to Python Live lesson
- Programming Languages and its types, Introduction to Python
- Basics of Python syntax & Concept
- Python Beyond Basics: Advanced Programming Techniques
- Python Session - 2 Live lesson
- Python Session - 3 Live lesson
- Python Session - 4 Live lesson
- Python Session 1 - Recording
- Python Session 2 - Recording
- Python Session 3 - Recording
- Python Session 4 - Recording
8. Machine Learning Algorithms 5 lesson(s)
- Machine Learning Algorithms Live lesson
- Recap of Machine Learning
- Supervised Learning Algorithms
- Unsupervised Learning Algorithms
- Reinforcement Learning Algorithms
9. Deep Learning Algorithms 4 lesson(s)
- Introduction to Deep Learning Algorithms Live lesson
- Recap to Neural Network & Deep Learning.
- Deep Learning Algorithms
- Deep Learning v/s Machine Learning
10. Natural Language Processing (NLP) 5 lesson(s)
- Natural Language Processing (NLP) Live lesson
- Introduction to NLP and Its Key Benefits
- Applications and Evolution of NLP
- Concepts of NLP: From Data Cleaning to Word Embeddings
- Case Study and Working of ChatGPT in NLP Applications
11. Computer Vision and AI Applications 4 lesson(s)
- Introduction to Computer Vision and AI Applications Live lesson
- Introduction and History of Computer Vision
- Human Vision vs. Computer Vision and Applications of Computer Vision
- Key Concepts in Computer Vision
12. Internet Of Things (IOT)4 lesson(s)
- Internet Of Things (IOT) Live lesson
- Introduction to IoT and Its History
- How IoT Works and Technologies Powering IoT
- IoT Applications, Benefits and Challenges, and Future Trends
13. AI and Robotics 4 lesson(s)
- AI and Robotics Live lesson
- Introduction to Robotics and AI Integration: History, Roles, Applications, Benefits, and Challenges
- Reinforcement Learning in Robotics
- Future Trends in AI and Robotics
14. Evaluation Metrics 3 lesson(s)
- Evaluation Metrics Live lesson
- Introduction to ML Model Evaluation and Its Significance
- Exploration of different evaluation metrics for assessing model performance.
15. Generative Adversarial Networks (GANs) and Autoencoders 5 lesson(s)
- Generative Adversarial Networks (GANs) and Autoencoders Live lesson
- What are Generative Adversarial Networks (GANs)?
- How GANs Work and Applications of GAN.
- Use cases of GAN.
- What are Autoencoders? And its Application
16. Final Assessment 1 lesson(s)
- Assessment
