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DSTC-A37 Online (e-LMS) Advanced Postgrad

Introduction to Big Data

by - DSTC

Master Introduction to Big Data in 4 weeks through hands-on, project-based online training with DSTC.

★★★★★ Be the first to review • 4 Weeks · 40 hrs • e-Certificate Included
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From ₹200 + GST

Programme Parameters

Educational Level:
Advanced Postgrad
Duration & Workload:
4 Weeks (40 Hrs)
Delivery Mode:
Online (e-LMS)
Prerequisites:
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.

About This Course

The Introduction to Big Data course is a free, beginner-friendly self-paced program designed to help learners understand how large-scale data is generated, processed, and used in modern systems. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.

🎯 Program Aim

The Introduction to Big Data course is a free, beginner-friendly self-paced program designed to help learners understand how large-scale data is generated, processed, and used in modern systems.

📋 Course Objectives

1. Put Artificial Intelligence techniques to work on real datasets and case studies.
2. Build a defensible project you can showcase to supervisors, reviewers, or employers.

👥 Who Should Enroll?

• Master's and senior undergraduate students specializing in Artificial Intelligence
• R&D engineers and working professionals applying Artificial Intelligence in industry
• Academics and educators building research or teaching capacity in Artificial Intelligence

🚀 Key Learning Outcomes

• A portfolio-grade Artificial Intelligence deliverable you can defend and extend.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.

💎 What You'll Gain

🎥

Live & Recorded Sessions

Lifetime access to class recordings
🎓

e-Certificate on Completion

Cryptographically verified credential
💬

Post-Programme Support

Direct access to mentors & council
💻

Hands-On Experience

Notebooks, real-world code & datasets

Curriculum Outline

Module 1 Outline

Introduction to Big Data

What is Big Data? • Characteristics of Big Data: Volume, Velocity, and Variety • Importance of Big Data in Modern Systems • Applications of Big Data

Module 2 Outline

Sources and Types of Data

Structured vs Unstructured Data • Data from Social Media, Sensors, and Systems • Data Generation and Collection • Importance of Data Quality

Module 3 Outline

Big Data Processing Basics

How Big Data is Stored and Managed • Introduction to Data Processing Concepts • Batch vs Real-Time Processing: Basic Idea • Overview of Data Pipelines

Module 4 Outline

Big Data Analytics

Understanding Data Analysis at Scale • Extracting Insights from Large Data • Basic Idea of Predictive Analytics • Use Cases in Business and Technology

Module 5 Outline

Applications and Future Scope

Big Data in Business, Healthcare, and Finance • Role of Big Data in AI and Machine Learning • Career Opportunities in Big Data and Analytics • Mini Learning Activity / Concept-Based Practice

Technical Specifications

ParameterRequirement
Covered Tool / PlatformBig Data
Covered Tool / PlatformData Storage
Covered Tool / PlatformData Processing
Covered Tool / PlatformData Analytics
Covered Tool / PlatformData Systems

Frequently Asked Questions

Yes. This is a free online self-paced course designed for beginners.

No. The course focuses on concepts and does not require prior programming experience.

You will learn big data fundamentals, including data types, processing, storage, and analytics concepts.

Students, beginners, and professionals from any background can join.

Yes. Learners receive an e-Certification after completing the course.

Big Data refers to very large and complex datasets that are generated from many sources and require special methods for storage, processing, and analysis.

The main characteristics of Big Data include volume, velocity, and variety, which describe the size, speed, and different forms of data generated in modern systems.

The Introduction to Big Data course is designed as a 2–3 week online self-paced course.

Yes. Big Data supports AI and machine learning by providing large volumes of information that can be used to identify patterns, train models, and generate insights.

The course explains big data, data sources, storage, processing, analytics, and real-world applications in simple language without requiring programming or prior technical experience. The Introduction to Big Data course provides a simple and structured foundation in understanding large-scale data systems and analytics. It is an ideal starting point for learners who want to explore data engineering, analytics, and modern data-driven technologies.

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