Big Data and Advanced Analytics

Embark on an 8-week journey into the world of Big Data and Advanced Analytics. Dive deep into big data technologies like Hadoop and Spark, learn the art of data processing and analysis, and harness the power of predictive analytics.

Conclude your training with a capstone project where you'll apply your skills to a real-world analytics challenge. Prepare to embark on a career in data science and analytics with our comprehensive program.

Big Data and Advanced Analytics Training

Duration: 8 Weeks (2 Days/Week)

Week 1: Introduction to Big Data

Day 1: Understanding Big Data

  • Introduction to big data concepts and challenges.

  • Overview of the training program and learning objectives.

Day 2: Big Data Technologies

  • Exploring big data technologies like Hadoop and Spark.

  • Handling large datasets and distributed computing.

Week 2: Hadoop and MapReduce

Day 3: Introduction to Hadoop

  • Understanding Hadoop architecture and components.

  • Setting up a Hadoop cluster for data processing.

Day 4: MapReduce Programming

  • Basics of MapReduce programming.

  • Implementing MapReduce jobs for data analysis.

Week 3: Apache Spark Fundamentals

Day 5: Introduction to Apache Spark

  • Overview of Spark and its advantages.

  • Setting up a Spark cluster.

Day 6: Spark Data Processing

  • Data manipulation with Spark RDDs.

  • Building Spark applications for data analysis.

Week 4: Advanced Analytics with Spark

Day 7: Spark Machine Learning (MLlib)

  • Exploring Spark's MLlib library.

  • Building machine learning models with Spark.

Day 8: Real-time Data Processing with Spark Streaming

  • Introduction to Spark Streaming for real-time data analysis.

  • Implementing streaming data pipelines.

Week 5: Data Visualization and Insights

Day 9: Data Visualization Tools

  • Importance of data visualization in analytics.

  • Creating interactive visualizations with tools like Tableau.

Day 10: Advanced Data Visualization

  • Designing insightful dashboards and reports.

  • Effective storytelling with data.

Week 6: Predictive Analytics and Machine Learning

Day 11: Predictive Analytics

  • Understanding predictive modeling.

  • Implementing predictive analytics with Python and R.

Day 12: Machine Learning Models

  • Exploring various machine learning algorithms.

  • Model evaluation and validation techniques.

Week 7: Big Data Analytics Applications

Day 13: Text Analytics and NLP

  • Analyzing unstructured text data.

  • Natural language processing (NLP) applications.

Day 14: Time Series Analysis and Forecasting

  • Time series data analysis for forecasting.

  • Building predictive models for time-dependent data.

Week 8: Capstone Projects and Certification

Days 15-56: Capstone Project Development

  • Apply your knowledge to a real-world big data analytics project.

  • Guidance from instructors.

  • Regular progress reviews and consultations.

Days 57-58: Capstone Project Presentations and Certification

  • Teams present their projects to industry experts.

Contact us to book this course

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