Preamble

In today’s data-driven world, organizations are leveraging big data and data science to gain valuable insights, drive decision-making, and achieve a competitive edge. This training program provides participants with a deep understanding of big data concepts, tools, and methodologies used in data science. Through practical sessions and real-world case studies, participants will learn how to analyze complex data, build predictive models, and apply machine learning techniques for solving business challenges.

Training Objectives

1. Introduce participants to big data concepts, tools, and technologies.
2. Develop skills in data collection, cleaning, analysis, and visualization.
3. Equip participants with practical knowledge of machine learning and predictive analytics.
4. Enhance the ability to apply data science techniques in solving real-world problems.
5. Build a foundation for working with big data platforms such as Hadoop and Spark.

Training Content

Module 1: Introduction to Big Data and Data Science

• Big data concepts, architecture, and ecosystem
• Introduction to data science and its applications
• Overview of big data technologies (Hadoop, Spark, NoSQL)

Module 2: Data Collection and Preprocessing

• Data sources and acquisition techniques
• Data cleaning, transformation, and integration
• Exploratory data analysis (EDA)

Module 3: Data Visualization and Analytics

• Tools for data visualization (Tableau, Power BI, Python visualization libraries)
• Descriptive and diagnostic analytics
• Communicating insights through visual storytelling

Module 4: Machine Learning and Predictive Modeling

• Introduction to machine learning concepts
• Building predictive models (regression, classification, clustering)
• Model evaluation and performance metrics

Module 5: Big Data Platforms and Real-World Applications

• Working with Hadoop and Spark
• Case studies in various industries (finance, healthcare, marketing)
• Ethical considerations and data security

Final Assessment & Certification

Participants will be assessed through hands-on projects and a final practical test. Upon successful completion, they will receive a certificate of competence in big data and data science.

Target Audience

• Data Analysts and Scientists
• IT Professionals and Software Engineers
• Business Analysts and Project Managers
• Academics and Researchers
• Anyone interested in big data and data science

Training Methodology

• Lectures and Presentations – Delivered by industry experts
• Hands-On Exercises and Projects – To apply knowledge in real-world scenarios
• Case Studies and Group Discussions – For problem-solving and experience-sharing
• Practical Demonstrations – Using big data tools and platforms
• Peer Collaboration and Networking – For diverse perspectives and learning