Introduction to Data Science

Introduction to Data Science

Overview
Curriculum
Reviews

At a Glance

Introduction to Data Science" is a foundational program designed to provide participants with a comprehensive understanding of the principles, techniques, and applications of data science. Participants will explore key concepts, tools, and methodologies used in data science, preparing them for further exploration in this rapidly evolving field.

Objectives

By the end of the course, participants will be equipped to:

  • Understand the role of data science in extracting insights and value from data
  • Gain familiarity with essential data science concepts, techniques, and methodologies
  • Apply basic statistical analysis and machine learning techniques to solve data-driven problems
  • Explore data visualization techniques to communicate insights effectively
  • Develop a foundational understanding of programming languages such as Python/R
  • Identify opportunities for leveraging data science to drive innovation and solve real-world problems

Prerequisite

No prior experience in data science is required. Basic knowledge of statistics and programming concepts is helpful but not necessary. Participants should have a curiosity and willingness to learn about data science and its applications.

Curriculum

  • 8 Sections
  • 0 Lessons
  • 0 Quizzes
  • 0m Duration
Expand All
Introduction to Data Science
0 Lessons0 Quizzes
Data Acquisition and Cleaning
0 Lessons0 Quizzes
Exploratory Data Analysis (EDA)
0 Lessons0 Quizzes
Introduction to Statistical Analysis
0 Lessons0 Quizzes
Introduction to Machine Learning
0 Lessons0 Quizzes
Data Visualization
0 Lessons0 Quizzes
Introduction to Programming for Data Science
0 Lessons0 Quizzes
Applications of Data Science
0 Lessons0 Quizzes
0 out of 5

0 user ratings

Deleting Course Review

Are you sure? You can't restore this back

Course Access

This course is password protected. To access it please enter your password below:

Related Courses

R Programming for Data Science

0 (0)
  • R programming fundamentals
  • Data science techniques in R
0m
0
0
0
Scroll to Top