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

What you will learn

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

Description

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the โ€œsexiest job of the 21st centuryโ€?

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, youโ€™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.


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Through different exercises, youโ€™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 donโ€™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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English
language

Content

Introduction to Data Science

What is Data Science ?
Data Science Workflow
Applications of Data Science Part 1
Applications of Data Science Part 2
Practice : Examples of Machine, Deep Learning and Internet Of Things
Data Science roles and tools
Quiz

Data Collection & Storage

Data Types Part 1
Data Types : Part 2
Data Collection
Data Storage
Data Pipeline
Multiple Choice Questions

Data Prepration, Data Exploration And Visualization

Data Cleaning
Practice : Retail Sales
Practice : Sentiment Analysis
Exploratory Data Analysis (EDA)
Practice : Count Data Points
Visualization & Dashboards
Practice : 100m world record

Experiment And Predict

Hypothesis Testing
Practice : Social Media Campaign
Supervised Learning
Practice : Identify Supervised ML
Practice : Select the right model
Unsupervised Learning
Practice : Identify Unsupervised ML