Data Science

Data Science Overview

This course is designed to provide students with a comprehensive understanding of data science. Students will learn about the fundamentals of data science, including statistical analysis, data mining, machine learning, and data visualization. They will also learn about various data science tools and technologies, including R programming language, Python, SQL, and data visualization tools. The course will cover a range of data science applications, including data wrangling, data exploration, data cleaning, and data modeling.

480 Hours of Sessions

240 Hours of Labs

Flexible Schedule

Free Demo On Request

24/7 Lifetime Support

One-on-One Doubt Clearing

Data Science Course Curriculum

Introduction to Data Science

Overview of data science
The role of data science in business decision-making
Advantages and challenges of using data science

Fundamentals of Statistics

Introduction to statistical analysis
Understanding statistical concepts and terminology
Probability theory and distributions

Data Mining and Machine Learning

Introduction to data mining and machine learning
Understanding machine learning algorithms
Building machine learning models

Programming for Data Science

Introduction to programming languages for data science
R programming language
Python programming language

SQL for Data Science

Introduction to SQL
Retrieving and modifying data using SQL
Creating and managing database objects using SQL

Data Wrangling and Exploration

Introduction to data wrangling and exploration
Data cleaning techniques
Exploring data using visualizations

Data Modeling and Evaluation

Introduction to data modeling and evaluation
Understanding the principles of model selection and evaluation
Applying modeling techniques to real-world problems

Request for more information

Project Work and Presentations

Students will apply the skills and knowledge gained in the course to design and develop a data science project. They will present their projects to the class, and receive feedback from their peers and the instructor.