Program Curriculum

• Module 1

  Python for Data Science

  Dive into Python’s data types, structures, and libraries like Pandas and NumPy, and learn to perform data manipulation, analysis, and visualization.

  Business Analytics using Excel

  Master Excel’s formulas, functions, and data visualization tools, and explore data analysis techniques like PivotTables and advanced charting.

  Power BI

  Learn data modeling, DAX, and visualization in Power BI, and understand how to connect to various data sources and publish reports.

  Tableau

  Understand Tableau’s interface, data types, and visualization techniques, and learn to create interactive dashboards and stories.

  Essential Statistics

  Cover descriptive and inferential statistics, probability distributions, hypothesis testing, and data interpretation.

• Module 2

  R for Data Science

  Explore statistical computing and graphics, including data manipulation, analysis, and visualization using R’s extensive package ecosystem.

  Data Analysis using SQL

  Learn to query and manipulate data within relational databases, understand data types, and optimize SQL queries for data analysis.

  Predictive Analytics (PA)

  Delve into statistical techniques to forecast future events, utilizing historical data, data mining, and machine learning algorithms.

  Use Case

  Understand the creation of use case diagrams to represent system functionalities and user interactions in system design.

  Learning Analytics (LA)

  Study the measurement and analysis of educational data to optimize learning and educational environments.

• Module 3

  Time Series

  Explore forecasting models like ARIMA, and understand concepts like seasonality and trend analysis for time-dependent data.

  Deep Learning

  Delve into neural network architectures, including CNNs and RNNs, and learn about backpropagation and dropout techniques for model optimization.

  Natural Language Processing (NLP)

  Study text pre-processing, sentiment analysis, and language modeling, along with the use of transformers like BERT for advanced NLP tasks.

  Analytic Process Automation (APA)

  Learn about automating data preparation, analytics, and business processes, and understand the role of AI and machine learning in enhancing APA solutions.

• Module 4

  Big Data

  Learn about data processing tools and techniques, and explore the ethical implications and security challenges of handling large-scale data.

  Domain Training on HR Analytics

  Understand the application of analytics in HR for talent management, performance analysis, and recruitment strategies.

  Computer Vision

  Delve into image processing, object detection, and advanced techniques like 3D reconstruction and machine learning in vision applications.

  Essentials of General AI

  Cover the basics of machine learning, natural language processing, and the ethical considerations in AI deployment.

  Use Case

  Examine how use cases describe user-system interactions to accomplish tasks, including actors, goals, and system responses.