Overview – Data Analytics with Generative AI Program

The six-month, online Student Training cum Internship Program in Data Analytics with Generative AI, is designed for students and early professionals aiming to build a strong career in data analytics.

With the global data analytics market projected to reach ₹10 lakh crore by 2029, organizations across finance, healthcare, retail, and technology are increasingly relying on data-driven insights for strategic decision-making. At the same time, AI-powered analytics roles are expected to grow by over 30% by 2026, making Generative AI a critical skill for future analysts.

This program delivers a dual skill set in Data Analytics and Generative AI, combining strong analytical foundations with modern AI-driven techniques. The industry-focused curriculum, co-designed with IBM experts, blends theory with hands-on practice through real-world case studies and projects.

Learners will gain practical expertise in data visualization, SQL, Python, exploratory data analysis (EDA), predictive modeling, and AI-powered analytics, along with access to 10X Club masterclasses, hackathons, AMA sessions, and industry-recognized certifications.

Training Approach

Practical-First Learning Experience

Hands-on implementation of every concept through labs, assignments, and real-world analytics projects.

Live Interactive Training

25–30 instructor-led live sessions per month focused on discussion, problem-solving, and personalized feedback.

Weekend Flexible Schedule

Designed for students and working professionals with weekend-focused live classes.

Industry-Based Tools Exposure

Practical experience with Python, SQL, Power BI, Tableau, IBM watsonx.ai, LangChain, Hugging Face, and cloud-based analytics tools.

Certification-Compliant Training

Curriculum aligned to major industry certifications, ensuring learners are job-ready.

What is Data Analytics?

Data Analytics is the practice of collecting, processing, and analyzing data to uncover insights, patterns, and trends that support informed decision-making.

It combines statistical analysis, data visualization, and predictive modeling to transform raw data into actionable business intelligence. With the integration of Generative AI, modern data analytics enables faster insights, automated reporting, intelligent forecasting, and natural-language interaction with data systems.

Features of Data Analytics

• Data-driven decision making across business domains

• Data Collection & Cleaning: Preparing raw data from multiple structured and unstructured sources

• Exploratory Data Analysis (EDA): Identifying trends, patterns, and anomalies

• Data Visualization: Creating meaningful dashboards and visual insights

• Statistical Analysis: Validating trends using statistical techniques

• Predictive Analytics: Forecasting future outcomes using historical data

• Generative AI Integration: AI-powered insights, automation, and code generation

• Automation & Reporting: Automated data pipelines and business reporting

• Monitoring & Optimization: Continuous improvement of analytical models

What You’ll Learn

• Excel & Data Handling: Data cleaning, formulas, pivot tables, and advanced Excel analytics

• SQL & Databases: Optimized queries, joins, subqueries, and window functions

• Python for Data Analytics: Data analysis using NumPy, Pandas, and Matplotlib

• Exploratory Data Analysis (EDA): Handling missing values, outliers, and feature analysis

• Data Visualization & BI Tools: Interactive dashboards with Power BI and Tableau

• Statistics for Analytics: Probability, hypothesis testing, regression, and correlation

• Machine Learning Basics: Regression, classification, clustering, and model evaluation

• Generative AI for Analytics: AI-generated SQL, Python code, insights, and reports

• Prompt Engineering: Designing prompts for analytics, visualization, and automation

• Automation in Analytics: AI-driven data cleaning, reporting, and insight generation

• Ethics & Responsible AI: Bias, data privacy, transparency, and governance

• Capstone Project: End-to-end real-world analytics project using GenAI

Eligibility for the Data Analytics Program

Who Can Apply

• Aspiring Data Analysts and Business Analysts

• IT professionals transitioning into analytics roles

• Software developers interested in data-driven decision making

• Finance, marketing, and operations professionals

• Fresh graduates starting a career in data analytics

• Professionals interested in AI-powered analytics and automation

Experience

• 0–2 years of experience is sufficient

• Prior IT or business exposure is an advantage but not mandatory

Skills

• Basic understanding of mathematics and logical thinking

• Familiarity with Excel or any programming language is helpful but not required

Devices Required

• Laptop or PC

• Stable internet connection for live sessions and hands-on labs