1. Faculty workshop ON Edge AI and ARM Inference Techniques

DATE: 11/12/2025

The Department organized a faculty workshop on Edge AI and ARM Inference Techniques, focusing on efficient deployment of AI models on resource-constrained edge devices. The sessions were conducted by expert speakers Ms. Muntaha Rouf, AI Engineer | Head, Center Of Excellence – Quantum Computing, Ms. Maroofa Yaseen (Data Scientist and Head Center Of Excellence IIOT), and Ms. Srishti, covering Edge AI fundamentals, ARM-based inference optimization, and practical approaches for building low-latency, real-world AI solutions.

2. Practical Agentic AI Design, Build, Deploy

The Department of Artificial Intelligence organized a two-day Summer School on Practical Agentic AI from 8 to 9 September 2025. The hands-on program was conducted by expert trainers Ms. Muntaha Rouf and Ms. Maroofa Yaseen, focusing on the design, development, and deployment of autonomous AI agents. Participants gained practical exposure to agentic architectures, tool integration, autonomous workflows, and real-world applications of Agentic AI in modern intelligent systems.

3. Next-Gen Blockchain Development , Learn, Build, Launch

The Department of AI organized  this hands-on workshop introduced participants to next-generation blockchain technologies, covering core concepts, development tools, and real-world applications. The sessions focused on learning blockchain fundamentals, building decentralized solutions, and understanding deployment strategies, enabling participants to gain practical insights into modern blockchain development.

4. PowerBI Basics: Turning Data Into Insights

The Department of AI organized a two-day hands-on workshop on Microsoft Power BI from 16 to 17 April 2025 at the B-Block Seminar Hall. The workshop was conducted by expert speakers Ms. Muntaha Rouf, and Ms. Maroofa Yaseen, focusing on data import, cleaning, modeling, DAX, and interactive dashboard development. Participants gained practical experience in transforming raw data into meaningful insights and creating professional, data-driven reports using Power BI.

5. Summer School: Blockchain for NextGen Security

The Department of Artificial Intelligence conducted an online Summer School on “Blockchain for NextGen Security” from 8 to 14 July 2025. The program was led by experts  Ms. Muntaha Rouf- (AI Engineer and Head Centre Of Excellence Quantum Computing), Ms. Maroofa Yaseen (Data Scientist and Head Center Of Excellence IIOT), introducing participants to blockchain fundamentals, security mechanisms, and real-world applications. The workshop provided valuable insights into how blockchain technologies enhance security, transparency, and trust in next-generation digital systems.

6. Faculty Development Program on Microsoft Power BI

The Department of AI conducted a Faculty Development Program on Microsoft Power BI on 29 May 2025 at the B-Block Seminar Hall. The hands-on program was led by expert speakers Ms. Muntaha Rouf, Ms. Maroofa Yaseen, and Mr. Dravid Nagi, focusing on data import, cleaning, modeling, DAX, and interactive dashboard creation. The FDP equipped participants with practical skills to analyze data effectively and develop professional, insight-driven Power BI reports for academic and administrative applications.

7.PowerBI basics: Turning Data into Insights

The Department of Artificial Intelligence organized a one-day hands-on Summer School workshop on 27 August 2025 at Delhi Technical Campus, focusing on the fundamentals of Microsoft Power BI. The session was conducted by expert trainers Ms. Muntaha Rouf- AI Engineer and Head Centre Of Excellence Quantum Computing, Ms. Maroofa Yaseen (Data Scientist and Head Center Of Excellence IIOT), who guided participants through data import, cleaning, modeling, basic DAX, and interactive dashboard creation. The workshop enabled participants to transform raw data into meaningful visual insights and build a strong foundation in data analytics and business intelligence.

8. Workshop on “CodeCraft – A Hands-On Fullstack Web Development with Flask”

The Department of Artificial Intelligence conducted a hands-on workshop on 17 April 2025 focused on fullstack web development using Flask. The session was led by Mr. Dravid Nagi , who guided participants through building dynamic web applications covering front-end design, backend logic, database integration, and deployment concepts. The workshop provided practical, end-to-end exposure to developing functional Flask-based web applications through live demonstrations and guided exercises.

9. “Data to Web: A Hands-on Bootcamp with Power BI & Flask”

The Department of AI, DTC organized a five-day hands-on bootcamp from 24 to 28 March 2025 aimed at bridging data analytics and web development. Led by expert speakers Ms. Muntaha Rouf- AI Engineer and Head Centre Of Excellence Quantum Computing, Ms. Maroofa Yaseen (Data Scientist and Head Center Of Excellence IIOT) & Mr. Dravid Nagi, the workshop trained participants in Power BI for data transformation, exploratory analysis, and interactive dashboard creation, along with an introduction to deploying analytics and machine learning outputs using Flask. The bootcamp enabled students to gain practical, end-to-end experience in converting data-driven insights into web-based applications.

10. Workshop on “AI and ML in First Year Labs” – Exploratory Data Analysis

The Department of Artificial Intelligence conducted a hands-on faculty development workshop focused on Exploratory Data Analysis (EDA). The session aimed to equip participants with practical skills in data preprocessing, visualization, and statistical analysis.

The workshop covered essential EDA concepts such as handling missing values, detecting outliers, and transforming data for analysis. Participants learned to create meaningful visualizations using tools like histograms, box plots, scatter plots, and heatmaps, gaining insights into data trends and relationships.

Through hands-on practice and interactive discussions, attendees developed a strong foundation in data analysis techniques, empowering them to incorporate AI and ML concepts more effectively into first-year lab sessions.

11. Two-Day Faculty Development Session on "Integration Of AI And ML In First Year Labs

The Department of Artificial Intelligence conducted a two-day hands-on faculty development workshop focused on the integration of machine learning—specifically regression models—into the mathematics curriculum for first-year students. Designed to bridge theoretical understanding with applied learning, the workshop offered a balanced blend of conceptual instruction and practical implementation.

This workshop empowered faculty to confidently incorporate AI and ML concepts into foundational mathematics courses, helping to enhance student engagement and build a strong analytical mindset from the start of their academic journey.

12. Two-Day Faculty Development Session on "Use Of Regression Machine Learning Model In Maths

The Department of Artificial Intelligence organized a two-day faculty development workshop focused on the application of regression-based machine learning models in mathematical problem-solving. This program provided participants with both theoretical grounding and hands-on experience in implementing regression techniques using real-world data. Faculty members actively engaged in implementing regression models using Python, interpreting performance metrics like R-squared and Mean Squared Error. The interactive nature of the sessions, combined with coding exercises and expert feedback, allowed participants to gain practical insights into integrating machine learning within mathematical contexts. The workshop successfully equipped attendees with the knowledge and skills required to apply regression models to solve real-world mathematical problems, enhancing their instructional and research capabilities.

13. Essentials Of Machine Learning Techniques

The Department of Artificial Intelligence conducted a multi-day Faculty Development Program covering key concepts and practical applications of Machine Learning and Artificial Intelligence. Sessions included Python essentials, EDA, feature engineering, regression (linear and logistic), clustering (k-Means, hierarchical), and classification algorithms such as Decision Trees, Random Forests, SVM, and k-NN.

Participants also explored deep learning basics, research paper writing tools, and engaged in hands-on coding exercises. The program concluded with a live project demonstration and doubt-clearing session, empowering faculty with applied knowledge for effective teaching and research in AI and ML.