This program will help you build foundational skills in data analysis, data visualization, programming, and Relational Database Management Systems (RDBMS).
Learners will learn how to apply basic statistical methods for data analysis using Excel. Including how to visualize data using graphs. Learners will also be introduced to RDBMSs and learn how to use SQL to retrieve or manipulate data. Then, they will learn to program using Python. Python has become a preferred programming language in the world of analytics.
This program will help learners as they progress through their academic journey. It will lay the foundation for an important programming and data analysis skill that will be of immense value in their academic and professional lives.
Course Curriculum
The Program focuses on competency development. It is practice based i.e. learners learn by doing things rather than by watching videos or by attending traditional lectures. Curriculum will cover the following
Data Analytics Using Excel
Learn to analyze numerical and categorized data using MS Excel as a tool. Use Descriptive Statistical techniques to analyze the data. Visually present the analysis using graphs & charts in MS Excel
Analytics using SQL
Learn to represent data in the form of tables in a Relational Database. Create, update, and retrieve data stored in a MySQL (RDBMS) database. Use Structured Query Language (SQL) to perform various operations on the database.
Introduction to Programming using Python
Learn to apply problem-solving techniques to decompose a problem into computational steps. Then translate the steps into a program using the Python language.
Python for Data Science (Using NumPy and Pandas libraries)
Use the NumPy and Pandas libraries in Python to perform data analysis.
Exploratory Data Analysis (EDA)
Introduction to Exploratory Data Analysis