AIML Training Program, Feb 2026 – B Batch

IHUB-DATA • IIIT HYDERABAD • PROGRAM SUCCESSFULLY COMPLETED

Congratulations, AIML Training Program – February 2026 (B Batch)!

Congratulations on successfully completing the 6-Month Artificial Intelligence & Machine Learning (AIML) Training Program conducted by iHub-Data, IIIT Hyderabad. Through expert-led lectures, hands-on notebook exercises, tutorials, assignments, and continuous assessments, you have built a strong foundation in Artificial Intelligence and Machine Learning.

This webpage celebrates the achievements of the February 2026 (B Batch) and marks the successful completion of your learning journey. We congratulate all participants and wish you continued success in your academic, research, and professional endeavors.

Program Successfully Completed

24 Weeks Completed • 5 Module Assessments • IIIT Hyderabad

✓ Machine Learning Fundamentals

✓ Advanced Machine Learning

✓ Deep Learning & Computer Vision

🎓 AIML Training Program Successfully Completed

Program Overview

AIML Training Program – February 2026 (B Batch) Successfully Completed

The AIML Training Program – February 2026 (B Batch) has been successfully completed after 24 weeks of intensive learning. Throughout the program, participants engaged in expert-led lectures, hands-on notebook exercises, tutorials, assignments, and five module assessments, covering a comprehensive range of Artificial Intelligence and Machine Learning concepts. This webpage highlights the achievements of the cohort and serves as a record of their successful completion of the program.

Program Details

Program Information

Program AIML Training Program – February 2026

Batch B Batch

Duration 24 Weeks (6 Months)

Schedule Every Sunday | 9:00 AM – 11:30 AM

Venue IIIT Hyderabad

Language English

Program Status Successfully Completed

Module Assessments 5 Completed

Certificates Issued to Eligible Participants

Completion 100% Completed

Learning Methodology

Program Delivery Approach

Expert-led lectures delivered by distinguished faculty members and industry professionals.
Hands-on learning through notebook-based practical exercises, tutorials, and coding demonstrations.
Continuous assessment through five module assessments, assignments, and practical learning activities.
Interactive doubt-clearing sessions and academic guidance provided by teaching assistants and the program coordination team.
Comprehensive learning experience combining theoretical concepts, practical implementation, and real-world AI/ML applications.

Curriculum Highlights

Key Learning Areas Covered Throughout the Program

Throughout the six-month AIML Training Program, participants developed a strong foundation in Artificial Intelligence and Machine Learning through expert-led lectures, hands-on notebook exercises, tutorials, assignments, and continuous assessments. The curriculum covered core machine learning concepts, data analysis and visualization, deep learning, computer vision, probabilistic learning, and advanced AI techniques, providing participants with both theoretical knowledge and practical experience.

Introduction to Machine Learning Data Transformation & Visualization Dimensionality Reduction K-Nearest Neighbours (KNN) Performance Evaluation Metrics Support Vector Machines (SVM) Multi-Layer Perceptrons (MLP) Ensemble Learning Regression Analysis Linear Regression & Regularization Convolutional Neural Networks (CNN) CNN & Transfer Learning Unsupervised Learning Naïve Bayes Classifier Gaussian Mixture Models Recurrent Neural Networks (RNN) Hands-on Notebook Exercises Tutorial Sessions Continuous Assessments

Assessment Overview

Performance Distribution Across All Five Module Assessments

Continuous assessments have been an integral part of the AIML Training Program, enabling participants to evaluate their conceptual understanding and practical skills throughout the course. The performance distribution below summarizes student achievement across all five completed module assessments.

Score Range (Out of 50)	Module 1	Module 2	Module 3	Module 4	Module 5
Top Tier (45–50)	31 participants	49 participants	51 participants	41 participants	48 participants
Strong Performers (40–44)	26 participants	11 participants	4 participants	19 participants	14 participants
Developing (35–39)	14 participants	1 participant	3 participants	4 participants	1 participant
Below 35	3 participants	1 participant	11 participants	1 participant	5 participants
Absent / Pending	15 participants	27 participants	20 participants	24 participants	21 participants

Assessment Summary: Five module assessments have been successfully conducted throughout the AIML Training Program to continuously evaluate participants’ understanding of key Artificial Intelligence and Machine Learning concepts. The assessment outcomes demonstrate consistent academic engagement and progressive learning across the six-month program.

Student Performance Portal

Participant Assessment Records

Search for your Hub ID or name to view your assessment performance across all five module assessments. An “A” indicates that the participant was absent for that assessment.

HUB ID	Full Name	A1	A2	A3	A4	A5
HUB2603B201	Aarti Dwivedi	A	48	50	47	45
HUB2603B202	Achi Venkata Vijaya Lakshmi	47	48	A	A	A
HUB2603B203	Akena Rupesh	46	48	50	46	46
HUB2603B204	Ananya Chanti	40	43	48	45	A
HUB2603B205	Annasagar Saicharan	44	46	46	44	44
HUB2603B206	B V Sai Lakshmi	43	45	38	39	39
HUB2603B207	Banala Sai Thrishar	A	A	33	41	42
HUB2603B208	Batthini Lakshmi Vengamamba Charitha	49	47	50	39	45
HUB2603B209	Bayyapu Spandana	46	48	50	48	46
HUB2603B210	Bindhu Aashritha V	A	A	A	A	A
HUB2603B211	Bollavaram Kusuma Sree	46	48	50	46	A
HUB2603B212	Byreddy Sushank Reddy	43	50	50	45	46
HUB2603B213	Chakali Abhilash	46	47	A	47	45
HUB2603B214	Challagundla Venkata Naga Sumanth	21	A	A	A	30
HUB2603B215	Chekkapalli Jhansi Lakshmi	46	A	A	A	46
HUB2603B216	Chilkuri Shreya Saanvi	37	42	42	43	40
HUB2603B217	Chitturi Pragathi	40	47	35	46	44
HUB2603B218	Devineni Adhyumna Chowdary	43	44	A	A	46
HUB2603B219	Dudekula Sharan Teja	47	48	48	47	45
HUB2603B220	Emmadi Tejaswi	40	45	47	45	44
HUB2603B221	Gandham Manuvarshitha	41	42	46	A	44
HUB2603B222	Gangiredla Sri Lasya	A	49	50	47	48
HUB2603B223	Gouda Sai Sri Chandana	46	47	48	44	46
HUB2603B224	Guduru Kritika Reddy	45	47	50	47	48
HUB2603B225	Gundamaraju Harshith Kashyap	44	A	50	47	45
HUB2603B226	Hafsah	49	48	49	47	46
HUB2603B227	Harshitha Sarvani Nimmagadda	39	48	48	43	47
HUB2603B228	Ithamraju Ojeswani	47	A	A	A	A
HUB2603B229	Kondam Rahul Reddy	47	50	43	46	45
HUB2603B230	Kandi Anurag	A	48	45	37	45
HUB2603B231	Kappagantula Srihitha	39	42	41	A	42
HUB2603B232	Kareedu Veekshitha Sai Sri	46	47	49	48	47
HUB2603B233	Katakam Pallavi	A	A	A	A	A
HUB2603B234	Kolli Jasmitha	43	A	A	47	47
HUB2603B235	Komarapu Santosh Lochan	44	41	46	39	42
HUB2603B236	Kommineni Viswateja	46	47	50	44	A
HUB2603B237	Kondreddy Geethika	43	45	A	47	47
HUB2603B238	Koride Ishanth	34	36	43	41	26
HUB2603B239	Korla Sumana Sri	A	46	A	A	A
HUB2603B240	Kote Swathi	A	A	A	A	A
HUB2603B241	Lakkoju Surya Uddish	43	48	32	43	46
HUB2603B242	Lakshmi Kavitha Anigani	47	47	50	46	A
HUB2603B243	Laranya Kandula	49	44	47	42	A
HUB2603B244	M Lakshmi Manas	44	47	50	48	45
HUB2603B245	Maddela Sahana Goud	49	47	50	47	A
HUB2603B246	Maganti Jahnavi	36	41	46	44	46
HUB2603B247	Mahesh Kompally	41	A	47	41	42
HUB2603B248	Md Fareesa Sultana	36	43	50	47	47
HUB2603B249	Mohammed Omair Ahmed	49	47	50	A	48
HUB2603B250	Mohammed Zubair	44	46	50	46	A
HUB2603B251	Monikanjali Tadepalli	43	48	50	45	44
HUB2603B252	Musanam Kausalya	47	A	50	44	A
HUB2603B253	N.Hema Harshitha	46	46	49	45	45
HUB2603B254	Nadimpalli Vanisha	40	A	48	46	44
HUB2603B255	Navadeep Saran Yadagiri	40	A	48	45	46
HUB2603B256	Neereti Tejaswini	A	49	A	A	A
HUB2603B257	Nikitha Reddy Nagireddy	45	49	50	45	48
HUB2603B258	Nitya Rajeswari Sarva	42	40	A	A	28
HUB2603B259	Nymisha Salivendra	46	48	50	A	46
HUB2603B260	P. Vishali	37	A	49	45	45
HUB2603B261	Pasupuleti Geethika	36	A	14	11	46
HUB2603B262	Patha Sai Ashrith	44	46	31	45	46
HUB2603B263	Pinnapureddy Pranav Kumar	47	42	50	46	46
HUB2603B264	Polipalli Jayesh	48	49	50	46	48
HUB2603B265	Potru Sandhya Priya	A	A	A	A	A
HUB2603B266	Rapolu Dheeraj	43	48	50	44	45
HUB2603B267	Ravipudi Taruni	37	47	A	47	48
HUB2603B268	S Rudrakshini	40	48	33	43	45
HUB2603B269	Sai Yash Kankipati	39	47	48	44	14
HUB2603B270	Seerla Ganesh	44	A	A	A	45
HUB2603B271	Shaik Maimood	26	A	33	41	43
HUB2603B272	Shiva Shivarla	48	A	50	47	46
HUB2603B273	Shravani Settigari	A	47	50	47	47
HUB2603B274	Shreya Sari	A	47	33	46	47
HUB2603B275	Sree Hasini N	38	46	49	41	44
HUB2603B276	Sri Sai Balaji (Krish Arjun)	48	47	49	46	46
HUB2603B277	Sriram Aishwarya	47	47	50	48	45
HUB2603B278	Srislesha Ananthula	48	A	50	44	46
HUB2603B279	Srujitha Yatham	44	48	46	41	45
HUB2603B280	Suchay Joshi	39	A	28	A	A
HUB2603B281	T Vivek Singh	38	A	39	A	A
HUB2603B282	Toomu Anikeith	39	A	32	46	42
HUB2603B283	Tummala Jathinsai	37	33	34	A	33
HUB2603B284	Vaishnavi Logishetty	44	48	49	A	46
HUB2603B286	Vedika Atul Kulthe	46	A	A	A	A
HUB2603B287	Velishetty Greeshma	A	A	A	A	A
HUB2603B288	Yalamanchili Lokesh Chowdhary	A	A	A	A	A
HUB2603B289	Yanamadala Viditha	48	46	50	47	45
HUB2603B290	Yamala Reddy Thanusha	A	A	33	46	46

Institutional Reach

A diverse engineering student cohort across institutions

High-Volume Hubs

CVR College of Engineering, Institute of Aeronautical Engineering (IARE), BVRIT Hyderabad College of Engineering for Women, Chaitanya Bharathi Institute of Technology (CBIT), and Vardhaman College of Engineering continue to represent major participation hubs in the cohort.

Wider Regional Footprint

VNR Vignana Jyothi, KMIT, Mahindra University, Vasavi College of Engineering, Anurag University, Osmania University, and premier national endpoints like SRM University and KL University reflect the broader institutional spread of the batch.

See the full list of participating institutions (44) + Expand

CVR College of Engineering
Institute of Aeronautical Engineering (IARE)
BVRIT Hyderabad College of Engineering for Women
Chaitanya Bharathi Institute of Technology
Vardhaman College of Engineering
CR Rao Advanced Institute of Mathematics, Statistics and Computer Science (AIMSCS)
Methodist College Of Engineering and Technology
Sreenidhi University Hyderabad
ACE Engineering College
VNR Vignana Jyothi Institute of Engineering and Technology
Neil Gogte Institute of Technology
Malla Reddy Deemed To Be University
GITAM Deemed To Be University
Keshav Memorial Institute Of Technology
M S Ramaiah University of Applied Science
Sridevi Women’s Engineering College
Mahatma Gandhi Institute of Technology
Guru Nanak Institutions Technical Campus
Gokaraju Rangaraju Institute of Engineering and Technology
Vidya Pratishthan’s Kamalnayan Bajaj Institute of Engineering and Technology
B V Raju Institute of Technology
Geethanjali College of Engineering and Technology
CMR College of Engineering and Technology
SR International Institute of Technology
KL University
Dhanalakshmi Srinivasan University
J.B Institute of Engineering and Technology
Chalapathi Institution of Engineering and Technology
Anurag University
Vasavi College of Engineering
Gokaraju Lailavathi Engineering College
Muffakham Jah College of Engineering and Technology
Vasireddy Venkatadri Institute Of Technology
SRM University, Andhra Pradesh
Mahindra University
Shadan Womens College Of Engineering And Technology
Central University Of Karnataka
St. Peters Engineering College
University College of Engineering, Osmania University
Rajeev Gandhi Memorial College of Engineering and Technology
MLR Institute of Technology
Koneru Lakshmaiah Education Foundation
Malla Reddy Engineering College for Women
KG REDDY College of Engineering & Technology

Beyond the Program

Continuing Your AI & Machine Learning Journey

Congratulations on successfully completing the AIML Training Program. Participants who have demonstrated strong academic performance, consistent engagement, and dedication throughout the course may be considered for upcoming 3–4 month Computer Vision internship opportunities, subject to eligibility and project requirements. We encourage all learners to continue building their AI skills through hands-on projects, research, and continuous learning.

Eligibility

Students completing the program with strong grades and maintaining the mandatory ≥75% attendance record will be eligible to apply for an exclusive 3- to 4-month online internship focused entirely on Computer Vision (CV) tasks.

What you’ll work on

Real-world object tracking and image segmentation datasets
Deploying state-of-the-art vision frameworks
Translating classroom ML & Deep Learning knowledge into live clinical / practical healthcare vision pipelines

Gallery

Program Completion

Important Information for Participants

Certificate of Competency

Certificates of Competency have been issued to participants who successfully fulfilled the program requirements, including the minimum attendance criteria and completion of the required module assessments.

Program Support

For any queries regarding certificates, participant records, assessment results, or other program-related matters, please contact the AIML Program Coordination Team. We will be happy to assist you.

Congratulations on Successfully Completing the AIML Training Program!

Congratulations to all participants of the AIML Training Program – February 2026 (B Batch) on successfully completing this six-month learning journey. Your dedication, perseverance, and enthusiasm have been instrumental in making this program a success. We hope the knowledge and practical skills gained throughout the course will serve as a strong foundation for your future academic, research, and professional endeavors in Artificial Intelligence and Machine Learning.

On behalf of iHub-Data, IIIT Hyderabad, we thank you for being a part of this program and wish you continued success in all your future pursuits.

Program Outcomes

Achievements Throughout the AIML Training Program

Successfully completed a comprehensive 24-week Artificial Intelligence and Machine Learning curriculum.
Participated in expert-led lectures, hands-on notebook exercises, tutorials, and practical learning sessions.
Completed five module assessments covering core and advanced AIML concepts.
Developed practical knowledge in Machine Learning, Deep Learning, Computer Vision, and Unsupervised Learning techniques.
Successfully fulfilled the program requirements and earned the Certificate of Competency (for eligible participants).