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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 ...Read more
Beginner
Online
₹ 499 799
Quick Facts
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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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
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
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