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Data Science for All : A foundation course

person icon Anmol

3.9

Data Science for All : A foundation course

Learn everything you need to know about fast-growing field of Data Science without having to write a single line of code

updated on icon Updated on Apr, 2024

language icon Language - English

person icon Anmol

English [CC]

category icon Data Science and AI ML,Artificial Intelligence,Machine Learning,Development

Lectures -26

Duration -1.5 hours

3.9

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Course Description

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the “sexiest job of the 21st century”?

Welcome to the Data Science for All course, where you will learn everything that you need to know about this rapidly growing exiting field of DS.

I am Anmol Tomar, a Data Scientist with over 6 years of experience in Data Science. I have worked with various fortune 500 clients in various domains such as retail, insurance, banking and helped them take data driven decisions. 

In this non-technical course, you’ll be introduced to everything you were ever too afraid to ask about this fast-growing and exciting field, without needing to write a single line of code.

Through different exercises, you’ll learn about the different data scientist roles, foundational topics like hypothesis testing, deep learning, machine learning, and how data scientists extract knowledge and insights from real-world data. So don’t be put off by the buzzwords. Start learning, gain skills in this hugely in-demand field, and discover why data science is for all!

I have designed this course for anyone who wants to understand the holistic view of the field of Data Science. By the end of this course, you will be able to confidently apply DS to the real world business problems.


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Goals

What will you learn in this course:

  • What is Data Science
  • Applications of Data Science
  • Data Science Workflow
  • Jobs and skills in Data Science
  • Data Science case studies
  • Applications of Machine learning
  • Applications of Artificial intelligence
  • Applications of Internet of things (IOT)
  • Data Collection and Storage
  • Supervised Learning
  • Unsupervised Learning

Prerequisites

What are the prerequisites for this course?

  • No prior knowledge required.
Data Science for All : A foundation course

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction to Data Science
7 Lectures
  • play icon Course Overview 01:59 01:59
  • play icon What is Data Science ? 06:01 06:01
  • play icon Data Science Workflow 06:01 06:01
  • play icon Applications of Data Science Part 1 04:36 04:36
  • play icon Applications of Data Science Part 2 06:00 06:00
  • play icon Practice : Examples of Machine, Deep Learning and Internet Of Things 02:25 02:25
  • play icon Data Science roles and tools 07:09 07:09
Data Collection and Storage
5 Lectures
Tutorialspoint
Data Prepration, Data Exploration And Visualization
7 Lectures
Tutorialspoint
Experiment and Predict
7 Lectures
Tutorialspoint

Instructor Details

Anmol

Anmol

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