The Absolute Beginners Guide to Data Science

BY
Udemy

Are you a beginner who wants to learn data science? Join the online Absolute Beginners Guide to Data Science course by Udemy.

Lavel

Beginner

Mode

Online

Fees

₹ 499 799

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

The Absolute Beginners Guide to Data Science Course is an online course designed exclusively for absolute beginners to learn and explore data science along with all the must-have knowledge and skills of a professional data scientist. The curriculum of  The Absolute Beginners Guide to Data Science Online Course developed by Sai Acuity Institute of Learning Pvt Ltd Enabling Learning Through Insight! will help the students to build a strong foundation of mathematics and statistics to make the data science journey easy and simple. 

The Absolute Beginners Guide to Data Science Certification provides the learners with a detailed understanding of Data Visualization, Python Programming, Matrix Algebra, Coordinate geometry,  Calculus, Data distribution, etc. The online course consists of Q&A support, all the skills a data scientist must-have, a certificate of completion, and many more. 

The highlights

  • Online course
  • Downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of completion
  • English videos
  • 30-Day Money-Back Guarantee

Program offerings

  • 41.5 hours on-demand video
  • 1 downloadable resource
  • Full lifetime access
  • Access on mobile and tv
  • Certificate of completion
  • English videos
  • Assignments

Course and certificate fees

Fees information
₹ 499  ₹799
certificate availability

Yes

certificate providing authority

Udemy

Who it is for

What you will learn

After the completion of The Absolute Beginners Guide to Data Science Online Certification, the learners will be able to study machine learning, CRISP-DM Framework, Descriptive & Inferential Statistics, and the like. Plus, the students will gather the skills of problem-solving, a methodical and logical approach, the process of interpreting and analyzing data, etc. 

The syllabus

Introduction

  • Introduction

Curriculum of Data Science

  • Curriculum and Lesson Plan

Practical Scenario 1

  • Scenario 1

Practical Scenario 2

  • Introduction Continued

Data Science Roles

  • Data Science Roles

An Insight on Data Science

  • Understanding Data Science: Octagonal Technical Facets

Terminologies and Statistical Methods in Data Science

  • Statistical methods and Terminologies in Data Science

Confusion Matrix, Random Variables

  • Random Variables

Descriptive Statistics

  • Introduction to Descriptive Statistics
  • Descriptive Stats Part 1

Understanding Percentile

  • Understanding Percentile
    • Assignment: Calculate the physical significance of percentile from 3 examples

Probability : An Introduction

  • Probability

Probability: Continued

  • Probability: Examples & Caselets

Descriptive stats continued

  • Descriptive stats

Degrees of freedom and mathematical operations

  • Learn the degrees of freedom, mathematical operations

Random Variables

  • Random Variables

Random variables contd

  • Random variables contd

Properties of E(x)

  • Properties of E(x)

Data Visualization

  • Data Visualization

Histogram and Boxplot

  • Histogram and Boxplot

Boxplot Contd and Scatter Plot

  • Boxplot examples and Scatter Plot

Covariance and Correlation

  • Covariance and Correlation

R Programming

  • R Studio
  • Installation of R
    • R Programming Part 1
    • R Programming Part 2
    • R Programming Part 3
    • R Programming Part 4
    • R Programming Part 5
    • R Programming Part 6
    • R Programming Part 7
    • R Programming Part 8
    • R Programming Part 9
    • R Programming Part 10
    • R Programming Part 11
    • R Programming Part 12

Refresher and Revisiting Basics

  • Revisit

Binomial Distribution

  • Binomial Distribution

Continuous Random Variables

  • Continuous Random Variables

Normal Distribution

  • Normal Distribution

Z table Distribution

  • Z table Distribution

Day 32: Central Limit Theorem - CLT

  • Day 32

Day 33: Decision Making

  • Day 33

Day 34: CRISP DM Framework

  • Day 34

Day 35: Test of Hypothesis

  • Day 35

Day 37: Recap of TOH

  • Day 37

Day 38: Statistical Methods

  • Day 38

Day 39: Anova

  • Day 39

Day 40: Anova Recap

  • Day 40

Day 41: Basics of Matrices, Coordinate Geometry, Calculus & Algebra

  • Day 41

Algebra and Calculus

  • Algebra and Calculus

Articles

Popular Articles

Latest Articles

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