Our Advance Data Science Program bridges academic learning with real-world industry practices. Learners gain conceptual knowledge, hands-on experience, and career preparation to become industry-ready professionals.
Achieve your learning goals with our expertly designed program, offering the practical knowledge and skills essential for success in your field.
Data Visualization & Reporting
Create interactive dashboards, reports, and visualizations to communicate insights effectively using tools like Power BI, Matplotlib, and Seaborn.
Machine Learning & AI Applications
Build, evaluate, and deploy machine learning models, AI solutions, and generative AI systems to solve real-world business problems.
Statistical & Analytical Skills
Apply descriptive and inferential statistics to understand trends, patterns, and relationships in data for informed decision-making.
Data Handling & Analysis
Master data collection, cleaning, manipulation, and analysis using Python, SQL, and Excel to extract actionable insights.
Comprehensive modules covering everything from fundamentals to deployment
The Fundamentals of Generative AI module introduces learners to the rapidly evolving field of AI that focuses on creating new, original content such as text, images, audio, and code. The module covers the theoretical foundations, key algorithms, and practical applications of generative AI in real-world scenarios.
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The Artificial Intelligence (AI) module introduces learners to the principles, techniques, and applications of AI in solving real-world problems. The module covers both the theoretical foundations and practical implementations of intelligent systems, providing a strong base for advanced analytics and machine learning projects.
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The Machine Learning module provides learners with the core theoretical knowledge and practical skills required to build predictive models and intelligent data-driven systems. The module covers the full machine learning workflow, from data preprocessing and feature engineering to model training, evaluation, and deployment.
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The Statistics for Data Science module builds the analytical foundation needed to understand, interpret, and model data effectively. This module introduces students to essential statistical concepts used in real-world data analysis, predictive modeling, and decision-making.
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The SQL module provides students with essential skills for managing, querying, and analyzing data stored in relational databases. Learners are introduced to database fundamentals, including tables, relationships, schemas, and normalization. The module focuses on writing efficient SQL queries to retrieve, filter, sort, and manipulate data.
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This course provides comprehensive training in Microsoft Excel, starting from basic spreadsheet operations and advancing to complex data analysis techniques. Students will learn essential functions, formulas, charts, data management tools, and reporting features. The advanced module covers pivot tables, advanced formulas, dashboards, macros, and automation techniques for professional-level data analysis. By the end of the course, learners will be able to efficiently organize, analyze, and present data for business decision-making.
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The Python Programming module builds the essential programming foundation required for data science and analytics. Students learn Python from the ground up, covering core concepts such as variables, data types, operators, conditional statements, loops, functions, and object-oriented programming. The module emphasizes writing clean, efficient code that supports data manipulation, automation, and analytical workflows.
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The Excel & Advanced Excel module equips learners with strong foundational and analytical skills using one of the most essential tools in data-driven industries. The module begins with core Excel functions such as data entry, formatting, formulas, functions, charts, and basic data organization techniques. Students learn how to efficiently manage and manipulate datasets using tables, sorting, filtering, and conditional formatting.
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Industry Experts: Working professionals deliver practical insights through real-world projects.
Academic Faculty: Highly qualified professors ensure strong theoretical foundations.
Build real-world projects and gain practical experience
6 real client projects across banking, FMCG, renewable energy & drone manufacturing — anonymised, industry-grade, and mentor-guided.
4 industry-relevant datasets spanning NBFC underwriting, retail sales, renewable energy forecasting & enterprise RAG — built for real-world model training.
The 6 month learning phase is a focused, intensive program designed to equip learners with the essential skills required for a career in data science and analytics. The curriculum combines foundational knowledge, practical exercises, and industry-relevant projects to ensure students gain hands-on experience across all core areas of the field.
3 months in-office internship with leading AI company phase offers learners a practical, industry-oriented experience to apply the knowledge and skills gained during the learning phase. This phase bridges the gap between classroom learning and professional work, allowing participants to work on real-world projects, datasets, and business challenges under the guidance of industry mentors.
Dedicated career coaching, mock interviews, and soft skills training
LinkedIn profile enhancement and resume workshops
Access to placement network with AI startups and technology companies
Potential for rapid growth based on performance and specialization
Get started in 3 easy steps
Fill out the Quick Online Application Form
Attend eligibility & orientation session
Confirm enrollment and complete fee payment
We offer easy EMI support to make quality education accessible for everyone
Start your journey to becoming a Advance Data Science Program expert today