Big Data Analytics

The Big Data Analytics course explores the tools and techniques used to analyze large datasets and extract actionable insights. It focuses on data mining, machine learning, and predictive analytics.

Key Learning Objectives

By the end of this course, students will:

• Understand Big Data Concepts: Learn the fundamentals of big data and its applications.
• Use Analytics Tools: Gain hands-on experience with tools like Hadoop and Spark.
• Apply Machine Learning: Build predictive models using big data.
• Interpret Data Insights: Translate data into actionable business strategies.

Core Topics Covered

1. Introduction to Big Data
   • Definition and characteristics of big data.
   • Applications in various industries.
2. Big Data Tools and Technologies
   • Hadoop, Spark, and other big data platforms.
   • Data storage and processing techniques.
3. Data Mining and Machine Learning
   • Techniques for data mining and pattern recognition.
   • Building and evaluating machine learning models.
4. Predictive Analytics
   • Applications in sales forecasting, customer segmentation, and risk analysis.
   • Case studies of predictive analytics in business.
5. Ethics and Challenges in Big Data
   • Data privacy and security concerns.
   • Ethical considerations in big data analytics.

Skills Acquired

By completing this course, students will:

• Analyze large datasets using big data tools.
• Build and evaluate machine learning models.
• Interpret data insights for business decision-making.
• Address ethical and privacy concerns in big data.

Career Opportunities

This course prepares students for roles such as:

• Data Scientist
• Big Data Analyst
• Business Intelligence Analyst
• Machine Learning Engineer
• Data Engineer

Why Choose This Elective?

This course is ideal for students who:

• Are interested in data science and analytics.
• Want to work with large datasets and advanced tools.

• Aspire to drive data-driven decision-making in organizations.