Participants will be taken through the relevant analytical tools needed

    ADVANCE EXCEL

Business Analytics with Excel: Introduction to Business Analytics,  Formatting, Conditional Formatting, and Important Functions , Analyzing Data with Pivot Tables, Power Query , Dashboarding , Data Analysis Using Statistics

    SQL

SQL, or Structured Query Language, is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS). SQL is the most common language used to access databases because it can work with any database:

 Introduction to SQL , Database Normalization and Entity Relationship (ER) Model ,Installation and SetUp ,Working with Databases and Tables, Working with Operators, Constraints, and Data Types , Functions in SQL, Subqueries, Operators, and Derived Tables in SQL ,Windows Functions in SQL ,Working with Views ,Stored Procedures and Triggers in SQL, Performance Optimization and Best Practices in SQL

    TABLEAU

This Tableau course helps you understand how to build visualizations, organize data, and design charts and dashboards to make more meaningful business decisions. You’ll be exposed to the concepts of data visualization, different combo charts and stories, working with filters, parameters and sets, and building interactive dashboards.

 Creating Charts in Tableau , Working with Metadata 17 , Filters in Tableau , Applying Analytics to the Worksheet ,Dashboards in Tableau , Modifications to Data Connections, Introduction to Level of Details in Tableau (LODS)

    MICROSOFT POWER BI

This is another widely used data visualization tool for data analysis similar to tableau. We will expose participants to the two most popular and widely used visualization tools in marketplace.

    PYTHON

This Data Science with Python course will establish your expertise of data science and analytics techniques using Python. With this Python for Data Science course, you’ll learn the essential concepts of Python programming and gain in-depth knowledge in data analytics, machine learning, data visualization, web scraping, and natural language processing. Python is a required skill for many data science positions, so jump start your career with this interactive, hands-on course.

Data Analytics Overview ,Statistical Analysis and Business Applications , Python Environment Setup and Essentials , Mathematical Computing with Python (NumPy) , Scientific Computing with Python (SciPy) ,Data Manipulation with Pandas, Machine Learning with Scikit-learn, Data Visualization in Python using Matplotlib,  etc

         R PROGRAMMING

    DATA SCIENCE CAPTONE PROJECT

     This Data Science Capstone project will give you an opportunity to implement the skills you learned throughout this program. Through dedicated mentoring sessions, you’ll learn how to solve a real-world, industry-aligned Data Science problem, from data processing and model building to reporting your business results and insights.

EXPECTED LEARNING/PROGRAM OUTCOME

At the end of the program we expect participants to be able to

    Gain an in-depth understanding of data structures and data manipulation

    Analyze data using linear and non-linear regression models and classification techniques

    Understand supervised and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipelines

    Perform mathematical computing using the NumPy, Pandas and scikit-learn packages

    Analyze data using Tableau , Power BI and become proficient in building interactive dashboards

    Undertake Capstone project which gives the opportunity to apply what you have learnt about how to make data driven decisions to real life business challenge.

TRAINING METHODOLOGY

The training shall focus on applied and practical methods by using the following concepts

Ø Involving participants in discussions and encouraging dialogue

Ø Use of templates for demonstration

Ø Use of case studies

Ø Open to questions from participants  in the course of the session

Ø Projects , exercises and assignments

Ø Serene and relaxed atmosphere

Ø  Excellent presentation and delivery

ELIGIBILITY

Degree or diploma in any field is required for this program. No prior experience in programming is required.

COURSE SCHEDULE

The program is run in sessions both in person and online options

In-Person Session (Morning ): Saturdays  9am – 1pm

Online Session: Sundays  3:30pm- 6:30pm

Weekday-Recap Session

COURSE DELIVERY

Duration: 18weeks

Frequency: Once per week

FACILITATORS

Faculty members are industry experts