About the Program
Data Analytics, tailored for IT graduates, revolves around the systematic collection, meticulous processing, and in-depth analysis of data to unearth invaluable insights. Data analysts employ a range of statistical techniques and wield powerful data visualization tools to derive meaningful interpretations that drive informed business decisions. This field stands as a linchpin for organizations aspiring to leverage the potential of data, seeking a strategic advantage, and fine-tuning their operations for optimal efficiency. With an acute understanding of data analytics, IT graduates position themselves at the forefront of the data revolution, poised to contribute significantly to the success and innovation of businesses in today's data-centric landscape.
Courses
    Credits Semester
  • Fundamentals of Data Analytics 3 III
  • Programming for Data Analytics (Python) 3 IV
  • Data Engineering Foundation with SQL and NOSQL 3 V
  • Artificial Intelligence and Machine Learning 3 V
  • Data Driven Storytelling and Visualization 3 VI
  • Social Media and Big Data Analytics 3 VII
  • Project Work - The Data Analytics Capstone: Exploring Data Insights with Analytics 3 VIII
    Credits Semester
  • IT World Essentials: Your Digital Entrypoint 3 I
  • Critical Thinking, Design Thinking, Leadership and Teamwork 3 II
  • Project Work - The Data Analytics Capstone: Exploring Data Insights with Analytics 3 VIII
    Credits Semester
  • Critical Thinking, Design Thinking, Leadership and Teamwork 3 II
  • Career Readiness in Digital Era 3 VI
Mode of Delivery
  • Self-paced learning – 10 hours
  • VILT sessions – 28 hours
  • Project work – 7 hours
  • Face-to-face instructor led sessions / VILT sessions (including project work) – 45 hours
  • Self-paced learning + Expert session – 30 hours
  • Project work – 15 hours
Job Roles
  • Data Engineer
  • Data Analyst
  • Data Scientist
  • Data Quality Analyst
  • Business Intelligence Analyst
  • Data Science Associate
  • Machine Learning Engineer
Software Tools
  • Python
  • RStudio
  • Tableau
  • Microsoft Power BI
  • MySQL
  • Microsoft Excel
  • MongoDB
  • Apache Spark
  • Apache Hadoop
Skills
  • Cleaning and preprocessing data for analysis, ensuring quality and consistency.
  • Applying advanced statistical methods and techniques for deriving meaningful data insights.
  • Creating interactive visualizations using Tableau, Power BI, and other data visualization tools.
  • Performing exploratory data analysis (EDA) to uncover patterns, correlations, and trends.
  • Wrangling and transforming raw data into usable formats for further analysis and modeling.
  • Communicating actionable insights through effective data storytelling and visual representations.