PGP in Big Data & AI for Business & Management
- Available in both Online & Offline format
- Weekend Classes
- Expert IIT-qualified faculties
- Generative AI and LLM based projects
- FORE Executive Alumni Status
- 3 Day campus immersion
Who can benefit from this Programme?
- New and experienced Data Scientists, Data Analysts, and Business Leaders
- Keen on enhancing data-driven decision-making and aligning AI strategies with organizational objectives
- Aspiring Data Scientists, AI Specialists, and Senior Managers
- Entrusted with leveraging big data and AI technologies for business innovation
- Technology Consultants and IT Professionals
- Seeking to harness advanced analytics and AI to drive digital transformation for client organizations
Programme Outline
135 hrs of comprehensive training
40 Projects
Project execution on Kaggle, Git Hub & Hugging Face
20+ practice workshops
Make your own LLM based RAG model
Programme Modules
- Python: Data structures in Python, Pandas, and Numpy.
- Data exploration, data summarization and transformation using pandas and numpy.
- Data Visualization: Data Visualization using Matplotlib, Seaborn and Plotly express. Developing relationships between mix of categorical and numerical features and plotting distributions
- Data Mining: Measures of Proximity; Cluster Analysis; Evaluation of Clusters: Cluster validation and Clustering Tendency; Curse of Dimensionality
- Techniques of Dimensionality Reduction: PCA, Random Projections and SVD (Singular Value Decomposition)
- Classification Analysis: Decision tree Induction & Regression Trees
- Random Forest algorithm
- Gradient Boosting Technique for Machine Learning
- Light GBM: Light Gradient Boosting Machine
- Extreme Gradient Boosting (XGBoost)
- Evaluating Classification: ROC, AUC, Precision, Recall, Specificity, Sensitivity; kappa metric; Overfitting; Bias-variance trade-off; L1 & L2 regularization
- Neural Networks
- Interpreting Machine Learning Models using Partial Dependence Plots and LIME
- Linux and Hadoop shell commands
- Introduction to Hadoop and its ecosystem
Hadoop file storage formats - Hadoop streaming
- Spark: Machine Learning, Structured Streaming, Deep Learning, Building data pipelines with Hadoop, kafka and NoSQL databases, Spark Delta Lake, and Using Spark NLP
- Apache Kafka: Building Data pipelines; transforming streaming data; Simple experiments with Apache Flink—Streaming analytics
- Introduction to NoSQL Databases and CAP theorem; Comparison with RDBMS
- Redis in-memory data structure store
- MongoDB Document Database
- Hbase column family database on hadoop
- TIG Stack: telegraf, InfluxDB and Grafana for collecting, storing and visualizing Time Series or IOT Data/metrics on a Dashboard
- Gephi Open Graph Visualization Platform
- Neo4j Graph Database
- Neural Networks
- Autoencoders and anomaly detection
- Deep Learning with Convolution Neural Network
- Using very Deep Convolution networks and Data Augmentation
- Transfer Learning-I
- Transfer Learning-II
- Natural Language Processing-I
- Natural Language Processing-II
- Recurrent Neural Networks
- General Architecture of Transformers
- Zero-shot classification and Few-shot learning
- Streamlit for developing LLM webApps
- Ollama and anythingLLM installation
- Embedding, vector databases and similarity search
- Prompt Engineering
- Developing LLM applications using langchain
- Biased LLMs and Ethics
Programme Director
Professor at FORE School of Management, New Delhi
Professor Ashok Harnal, with 31 years of work experience, holds a B.Tech from IIT Delhi and an M.Phil from Punjab University, Chandigarh. He has been teaching and experimenting with Big Data technology since around the last twelve years. During his stay in the Min of Defence, he has led country-wide projects like Raksha Bhoomi for land records and establishing Disaster Management organizations at Delhi and Pune. He has published two books (both by Tata McGrawHill ): One on How to Programme games on computers and the IInd on Linux Administration and Applications.
Faculty Members
Prof. Aman Nath Mitra
Associate Professor
Prof Shilpi Jain
Professor of Business Administration in the Information Technology & Big Data Analytics
Alumni Profiles & their Projects
Sheik M Imran
Intel Corporation (USA)
Bhaveshkumar Thaker
Tech Mahindra
Tapas Mohanty
Infosys
Devendra Yadav
Wallmart Labs
Ananda Deshmukh
Capgemini
Amukhta Gouru
Philip Morris ( Switzerland )
and many more
Shreedhar Neelaraddi
Samir Kumar
Carmen Rodriguez
Debasmita Mishra
Rituparna
Abhishek Kumar Gauraw
Ricardo Duran
Sreenivasa Chalamalasetty
Peal Das Gupta
Ravi Rokhade
Nidhi Wadhwa
Sandesh A K
Rohit Jain
Biswajyoti Majumdar
Digvijay Singh
Chandrasekaran Nageswaran
Velladurai
Vivek Datta
Past Participants of this Programme Work at
About collaboration of FORE and GradGurukul
FORE School of Management has entered into a collaboration with GradGuruKul, which serves as its exclusive marketing and learning partner. This partnership aims to leverage GradGuruKul's expertise in marketing and educational services to enhance FORE School of Management's outreach and educational offerings. GradGuruKul will play a pivotal role in promoting FORE School of Management's Programmes, facilitating learning initiatives, and fostering a stronger presence in the educational landscape through strategic marketing and educational support activities.