About Us

Great Learning offers a rigorous, industry-aligned Post‑Graduate Data Science program for graduates and early-career professionals. The program combines expert-led teaching, hands-on projects, and a structured curriculum covering modern tools and techniques. Learners gain job-ready skills in analytics, machine learning, AI, and data-driven decision-making, making it ideal for career advancement in data science roles.

Courses Offered

• PG Program in Data Science (with optional specializations such as Generative AI or Data Science & Engineering)

• Related tracks in AI, Machine Learning, Business Analytics, and data engineering

Course Highlights ✅

• Classroom and hybrid immersive training led by industry experts

• Curriculum from foundational statistics and programming to advanced machine learning and data engineering

• Real-world projects and a capstone project for portfolio development

• Career support including placement assistance, resume building, and interview preparation

• Flexible fee and installment options for financial accessibility

What Will I Learn?

• Core Data Science Skills: Python, SQL, data manipulation, and preprocessing

• Statistical & Analytical Foundations: Statistics, probability, exploratory data analysis (EDA), and visualization

• Machine Learning & Predictive Modeling: Regression, classification, clustering, time-series forecasting

• Specialization Modules: Generative AI or advanced data engineering (optional)

• Project Work: Hands-on, industry-relevant capstone projects for portfolio building

Career Benefits 🎯

• Prepare for roles such as Data Scientist, Data Analyst, ML Engineer, Analytics Consultant, or Data Engineer

• Post‑Graduate certification validates skills and strengthens your CV

• Real-world project portfolio to showcase practical abilities to employers

• Placement support with resume review, mock interviews, and job assistance

• Exposure to modern tools and workflows for long-term career growth in analytics and AI

Contact & Enrollment Details

• Program Format: Classroom-based, online, or hybrid depending on batch

• Duration: Approximately 5 months

• Fees: Contact admissions for fee structure and EMI options