Data Analytics

SITH Computer Institute
Last Update 20/09/2023

About This Course

  • The global data science platform market is growing due to advancements in big data technologies, a focus on gathering and analysing data for decision-making, and an increase in dependence on machine learning.
  • The adoption of data tools and technologies is contributing to business growth across the globe. The number of jobs requiring Data Science skills is expected to grow by 27.9% by 2026, according to the US Bureau of Labour Statistics.
  • As businesses continue to rely on the power of data, the need for skilled data scientists is also increasing.
  • With the rising demand for data science professionals, SITH Computers is pleased to introduce the job-assured Postgraduate Program in Data Science and Analytics.
  • Featuring custom learning modules, this 6-month program will help you learn data science and analysis from the ground up.
  • The program helps learners to master Data Science and write complex Machine Learning algorithms to solve real-world business problems.


Helpie FAQ

  • Basic Programming
    The module covers the basics of programming for non-programmers. Learn programming concepts and implement those concepts to write efficient code. Get introduced to Lists and OOPS concepts. What will you achieve?
    • Build a solid foundation for programming
    • Practice coding skills with 20+ coding questions
    • Introduction to Programming
    • Variables & Arithmetic Expressions
    • Functions
    • Data Types
    • Conditions & Conditional statements
    • Lists
    • OOPS
  • Module 1 - Excel
    The module covers the basics of Excel for data science. Learn Excel essentials to get a strong hold on using Excel for data analysis. Get introduced to pivot tables, formulae and charts. What will you achieve?
    • Build a strong foundation of Excel for data analysis
    • Summarise data with pivot tables and charts
    • Excel Basics
    • Excel Essentials
    • Formulae
    • Data Analysis
    • Charts
    • Pivot Tables
    • Lookup
  • Module 2 - SQL
    The module introduces learners to SQL programming. Learn how to query data from databases and create datasets for data analysis. What will you achieve?
    • Build a strong foundation of SQL for data querying
    • Create datasets for data analysis
    • DDL, DML, DQL statements
    • Aggregate, Date Functions
    • Union, Union All & Intersect Operators
    • Joins
    • Views & Indexes
    • Sub-queries
  • Module 3 - Python Programming
    The module introduces the learners to Python programming. Work with multiple Python data science libraries to execute essential tasks like mathematical calculations, data manipulation, etc. Learn data visualisation with Python. What will you achieve?
    • Master Python programming
    • Run data analysis process using Python libraries
    • Create useful charts for data visualisation
    • Python Objects, List
    • Functions
    • Numpy
    • Pandas
    • Data Frame Manipulation
    • Data Visualization
    • EDA
  • Module 4 - Data Visualisation with Tableau
    1. Introduction to Tableau | How Tableau Works | Tableau Courses
    2. Tableau - Download Desktop
    3. Tableau - Install Desktop
    4. Tableau - Connecting With Different Databases
    5. Tableau Vs Excel
    6. Tableau - Data Type
    7. Tableau - View Data
    8. Tableau - Column Formatting
    9. Tableau - Sort
    10. Tableau - Drill Down And Hirearchies
    11. Tableau - Sorting
    12. Tableau - Grouping
    13. Tableau - Measure Name And Values
    14. Tableau - Measure Names Usage
    15. Tableau - Discrete Vs Continous
    16. Tableau - Parameters
    17. Tableau - Combine
    18. Tableau - Sets
    19. Tableau - Title And Caption
    20. Tableau - Exporting
    21. Tableau - Granularity
    22. Tableau - Worksheet Interface
    23. Tableau - Managing Metadata
    24. Tableau - Cross Database Joins
    25. Tableau - Data Blending
    26. Marks Types
      • Color
      • Size
      • Label
      • Tooltip
      • Detail
    27. Font
    28. Alignment
    29. Shading
    30. Borders
    31. Introduction of charts
      • Scatter Charts
      • Word Maps
      • Line Chart
      • Bubble lines
      • Bar Chart
      • Stacked Chart
      • Tree Maps
      • Bump Chart
      • Waterfall
      • Pie Chart
  • Module 5 - Data Visualisation with PowerBI
    Introduction to Power BI   How to Download, Install and upgrade features in Power BI   Introduction to Basic Charts 1) Column Charts 2) Stacked Column Chart 3) Pie Chart 4) Dount Chart 5) Funnel Chart 6) Ribbon Chart   What is Included and Excluded in Power BI   View Data and Export   Map in Power BI A Basic Map In Power BI A Simple-Filled Map MAP with Pia Chart Formatting in MAP   Table and Matrix in Power BI 1) Creating a simple Table 2) Formatting in table 3) Conditional Formatting in Table 4) Changing Aggregation in Table 5) Creating a Matrix in Power BI 6) Conditional Formatting in Matrix 7) Automatic Hierarchy in Matrix 8) Subtotal and Grand Total 9) Number Formatting in Table and Matrix   Other Charts in Power BI Desktop 1) Line Chart 2) Drill Down in Line Chart 3) Area Chart 4) Line Vs Column Chart 5) Scatter Plot 6) Waterfall Chart 7) TreeMap 8) Guage Chart   Cards and Filters 1) Number Card 2) Text Card 3) Date Card 4) Multi-Row Card 5) Filter on Visual 6) Filter on Page 7) Filter on All Pages 8) Drill through   Slicers In Power BI 1) Slicer for Text 2) Format Text Slicer 3) Date Slicer 4) Format Date Slicer 5) Number Slicer   Objects and Actions(Hyperlinks) Insert Image Insert Text Insert Shapes Insert Buttons Action - Web URL Action - Page Navigation Action - Back Action – BookMark   Power BI Service Introduction 1) Creating a Superstore Report 2) Create an account on Power BI Service 3) Publish Report to Power BI Service Account 4) Export (PPT, PDF, PBIX) Report and Share 5) Comment, Share and Subscribe to a report 6) Create a dashboard in Power BI Service 7) Problem in Power BI Dashboard and Its Solution 8) Automatic Refresh - Data Gateway 9) Create a Report Directly in Power BI Service   Text Function in Power Query(Power BI) Merge Split and Trim Upper, Lower, and Proper Add Suffixes and Prefix Left, Right, and Mid Extract Text with Delimiter   Date Functions in Power Query(Power BI) Year,Quarter,Month,Day Difference Between Dates, Earliest and Latest Name of Day and Name of Month Day of Week/Month/Year & Week of Month/Year Extract Date from Date and Time Calculate Age in Button Clicks Number Functions in Power Query(Power BI) Add, Subtract, Divide, Multiply Percentage, Percent of, Modulo Rounding the numbers IsEven, IsOdd and Sign Conditional Columns in Power BI Conditional Column on One Column Conditional Column on two column Conditional Column comparing two column values Conditional Column on Dates   M Language in Power Query Introduction to M Language M Language – Date (ISIN) M Language – Date (Add and Subtract) M Language – Date (Day, Month, Week, Year) M Language – Text (Basic)      
  • Module 6 - Capstone Project
    Build a data science project on your own by applying the learning from the bootcamps. Learn planning the project and implementing it successfully. Present your project to a team of evaluators from the industry and get valuable feedback. Add the project to you GitHub project portfolio. What will you achieve?
    • Learn to plan a data science project
    • Solve a real-world problem using data science
    • Gain confidence on your skills by presenting the project to industry experts
    • Combination of all skills learned throughout the course
    • Project Presentation Skills
  • Module 7 - Career Services
    Prepare for interview opportunities by polishing the key skills. Get support to create your digital profile and resume. Sharpen your interview skills through interview preparation workshops and expert-based mock interviews. Resolve your career related queries through a mentorship session. At the end of the module, you will be ready for real interviews. What will you achieve?
    • Build an exciting resume and digital profile for recruiters
    • Sharpen your interview skills with mock interview sessions
    • Resolve any career-related queries to have clarity and confidence
    • Resume Building
    • GitHub Project Portfolio
    • Interview Preparation Workshops
    • Mock Interviews
    • Career Mentorship


    Learning Objectives

    Dedicated Career Services.
    Job-focused curriculum with Specializations.
    Live learning and peer discussions.
    Data Wars Hackathon and Data verse Project Competition.


    • All you need is a laptop, tablet or smartphone with an internet connection!