Data Science and Analytics

SITH Computer Institute
Last Update 29/03/2023

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 - Statistics for Data Science
    The module introduces the learners to statistics. Review, analyse, and draw conclusions from data. Apply quantified mathematical models to appropriate variables for data analysis. What will you achieve?
    • Build a strong statistics foundation
    • Analyse data and draw conclusions using statistics
    • Implement mathematical models for data analysis
    • Introduction to Statistics
    • Probability Theory
    • Probability Distributions
    • Hypothesis Testing
    • Statistical Tests
  • Module 5 - Machine Learning
    The module introduces the learners to machine learning and explains how different ML algorithms work. It also covers the optimisation of models and model tuning. Get a complete understanding of how organisations are applying ML to solve their problems and grow the business. What will you achieve?
    • Learn machine learning algorithms & their applications
    • Analyse data and make predictions
    • Solve real-world business problems using ML
    • Introduction to Machine Learning
    • Types of Machine Learning
    • Linear Regression
    • Optimization Techniques
    • Gradient Descent
    • Logistic Regression
    • Model tuning
    • Decision Trees
    • Random Forests
    • K-Means CLustering
    • Hierarchical Clustering
    • Principal Components Analysis (PCA)
    • Time Series
  • Module 6 - Data Visualisation with Tableau & PowerBI
    The module covers data visualisation with two popular business intelligence tools - Tableau and Power BI. Create charts to articulate data and present insights to the business. Learn to showcase a data-based story to the stakeholders. What will you achieve?
    • Master data visualisation with Tableau
    • Master data visualisation with Power BI
    • Create meaningful dashboards for the business
    • Introduction to Tableau
    • Tableau Interface and Chart Types
    • Visual Analytics with Tableau
    • Dashboard and Stories
    • Power BI Interface
    • Data Transformation
    • Data Modelling
    • Visual Data Analytics with Power BI
  • Module 7- Specialisation 1 - Advanced ML Track
    This module focuses on preparing the learners for placement based on their capability and performance during the course. Work on multiple projects with Project Mentor to sharpen your ML skills. Learn advanced ML concepts and AI fundamentals to enhance your profile. What will you achieve?
    • Sharpen ML skills through projects
    • Learn advanced ML skills
    • Get introduced to AI
    • ML Algorithms - Ensemble, Bagging, Boosting, KNN, SVM
    • Advanced ML - Naïve Bayes, Recommendation Engine
    • Introduction to Neural Network and AI
    • Computer Vision
    • NLP and Text Analytics
  • Module 7- Specialisation 2 - Data Analytics & ML Track
    This module focuses on preparing the learner for placement based on their capabilities and performance during the course. Work on multiple projects with a Project Mentor to sharpen your data analytics and ML skills. Learn big data analytics with Hadoop & Spark to enhance your profile. What will you achieve?
    • Sharpen ML skills through projects
    • Learn big data analytics with Hadoop
    • Execute machine learning with Spark
    • ML Algorithms - SVM, Association Rules
    • Practice Projects on ML
    • Big Data & Hadoop Framework
    • Machine Learning with Spark
    • Advanced SQL
  • Module 8 - 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 9 - 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!