Co Teaching Programs with Industry

Name of the Event: Dr. Mukul Joshi - Program Director IIT B Trust Lab

Course Code: BCER26PE01 Course Name: Deep Learning Credit: 4
Course Faculty: Dr. Sujata Kolhe
Resource Person Name: Mr. Guruprasad Pathak, AI Engineer, ATX Labs
No of Hours: 5 Hours
30/03/2026 10.00 am to 1.00 pm
16/04/2026 9.00 am to 11.00 am

Objective of the Event :
The primary objective of the co-teaching session was to provide students with practical insights and industry-oriented knowledge on Deep Learning. The session aimed to:

• Provide students with exposure to advanced deep learning architectures and generative models.
• Bridge the gap between theoretical concepts and industry-oriented AI applications.
• To guide students in applying deep learning concepts to their mini-projects.
• Enhance student’s problem-solving abilities in the domains of LLMs, generative AI, and sequence modeling.

Resource Person: Mr. Guruprasad Pathak
Mr. Guruprasad Pathak is an AI Engineer specializing in LLM/SLM Training, Monitoring & Inference Optimization, AI Evaluation, and RAG Pipelines. He is also an Oracle 2024 GenAI Certified Professional with strong expertise in problem solving and advanced AI systems. During the co-teaching sessions for the Deep Learning course, Mr. Pathak significantly contributed by delivering industry-oriented insights on advanced deep learning and generative AI concepts. He explained complex topics such as Autoencoders, GANs, Encoder-Decoder architectures, Transformers, BERT, and GPT using practical examples and real-world applications.

Number of Participants: 14

Brief Description of the Event :
Day 1: 30/03/2026
Topics Covered:

• Autoencoders
• Generative Adversarial Networks (GANs)
• Encoder-Decoder Architecture
• Transformers: BERT and GPT

Mr. Guruprasad Pathak also provided students with an assignment on “Tone Classification of Marathi Stories using BERT”. He explained the problem statement, dataset preparation, preprocessing techniques, and the application of BERT for text classification tasks. The assignment helped students understand the practical implementation of transformer-based models in Natural Language Processing (NLP) and encouraged them to explore language-specific AI applications using deep learning techniques.

Day 2: 16/04/2026
On Day 2, Mr. Guruprasad Pathak conducted an interactive doubt-solving session for the students. He discussed the “Tone Classification of Marathi Stories using BERT” assignment in detail and clarified students’ doubts related to dataset handling, preprocessing, model training, implementation challenges, and evaluation techniques. He also guided students on improving their approach towards transformer-based NLP projects and provided suggestions for effective mini-project implementation.

Outcomes:
1. Students understood the concepts of Autoencoders, GANs, Encoder-Decoder models, and Transformer architectures.
2. Students gained knowledge of transformer-based models such as BERT and GPT and their applications in NLP tasks.
3. Students understood the concepts of Autoencoders, GANs, Encoder-Decoder models, and Transformer architectures.
4. Students improved their understanding of dataset preprocessing, model training, evaluation techniques for NLP applications, and gained exposure to current industry practices and emerging trends in Generative AI and LLM.
5. Students received guidance for mini-project implementation and clarification of conceptual and technical doubts.

Department: Computer Engineering (Regional Language)
Course Code: BCER26PE04
Course: Cloud Computing
Credits: 3
Course Faculty: Mr. Ganesh Deshmukh
Resource Person: Mr. Ameya Vaidya
Total Hours: 8

Objective
To enhance students’ understanding of Cloud Computing through industry-oriented co-teaching

Schedule

Date	Time
05/02/2026	2-3 PM
10/02/2026	2-3 PM
12/02/2026	2-3 PM
03/03/2026	2-3 PM
05/03/2026	2-3 PM
17/03/2026	2-3 PM
31/03/2026	2-4 PM

Benefits :
Mr. Ameya Vaidya successfully delivered one complete unit of the Cloud Computing course as per the syllabus. The sessions combined theoretical concepts with practical insights, industry examples, and interactive discussions. Students actively participated throughout the sessions and gained a better understanding of cloud architecture, service models, deployment models, and real-world applications.

Outcomes

• Improved conceptual understanding.
• Exposure to industry practices.
• Better understanding of cloud technologies.
• Enhanced student engagement.

Conducted by: Mr.Kartik Pandey
Affiliation: Lead Product Designer YUJ Designs, Pune
Dates:

• 16 th Feb 2026, 11.10 to 01.10
• 17 th Feb 2026, 03.10 to 05.10
• 30 th March 2026, 11.10 to 12.10

Audience: Third-Year B.Tech Students
Course Incharge: Ms. VARSHA PANDAGRE
Topics Discussed

• UI Design principles:
• Introduction to Design Systems:
• Prototyping, Usability Testing, and UI Development
• User testing methods: heuristic evaluation, usability testing,

Outcomes
By the end of the co-teaching sessions, students:

• Understand and apply fundamental UI design principles in interface creation
• Explain the role and structure of design systems in modern UI development
• Develop basic prototypes for user interfaces
• Apply usability testing methods such as heuristic evaluation and user testing
• Analyze user feedback to improve interface design
• Demonstrate industry-relevant UI/UX design practices and workflows