Course curriculum
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1
Welcome to the course!
- About this course: Overview, Learning Outcomes, Who Should Enroll...
- Instructor bio - Pramod Gupta
- Key pointers for this program
- Joining the Alumni Community
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2
Module 1
- Module 1 - Introduction to Data Science
- Segment - 01 - Introduction to the Course
- Segment - 02 - Data Analysis and Data Mining
- Segment - 03 - Software Choices for Data Analysis
- Segment - 04 - What is R
- Segment - 05 - Steps in the Analytics Exercise
- Segment - 06 - Analytics Capabilities Framework
- Segment - 07 - The Job of the Data Scientist
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3
Module 2
- Module 2 - R Studio and Getting Started with R
- Segment - 08 - Getting Started with R and Installation
- Segment - 09 - Things to Know About R and Its Packages
- Segment - 10 - Getting a Feel for R Some Examples
- Segment - 11 - Lists and Factors
- Segment - 13 - DataFrame Basics
- Segment - 12 - Matrices
- Segment - 14 - Getting Data Into R and Managing Data
- Segment - 15 - Loops and Flow Controls
- Segment - 16 - Functions in R
- Segment - 17 - What to do When You Need Help
- Segment - 18 - R and R Studio in Action
- Segment - 19 - Vectorized Operations
- Segment - 20 - Matrices in R
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4
Module 3
- Module 3 - Data Manipulation Techniques - Part 1
- Segment - 21 - What is Data
- Segment - 22 - Types of Data Sets
- Segment - 23 - Preparing Data and Data Integration
- Segment - 24 - Handling Missing Data and Values
- Segment - 25 - Handling Outliers
- Segment - 26 - Data Transformation
- Segment - 27 - Handling Duplicate Data
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5
Module 4
- Module 4 - Data Manipulation Techniques - Part 2
- Segment - 28 - Getting to Know the Data
- Segment - 29 - Relationships Between Variables
- Segment - 30 - Data Aggregation
- Segment - 31 - Sub-setting
- Segment - 32 - Sorting and Ordering
- Segment - 33 - Merging Matrices and DataFrames
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6
Module 5
- Module 5 - Advanced Data Manipulation
- Segment - 34 - dplyr
- Segment - 35 - Other Functions in dplyr
- Segment - 36 - Still More Functions in dplyr
- Segment - 37 - Apply Function
- Segment - 38 - What is Data Visualization
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7
Module 6
- Module 6 - Visualization
- Segment - 39 - Graphics in R
- Segment - 40 - Graphing Basics in R
- Segment - 41 - ggplot
- Segment - 42 - ggplot2
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8
Module 7
- Module 7 - Probability and Estimation
- Segment - 43 - Probability Distributions
- Segment - 44 - Probability Distributions
- Segment - 45 - Sampling Techniques
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9
Module 8
- Module 8 - Statistical Tests and Hypothesis Testing
- Segment - 46 - Statistical Tests and Hypothesis Testing
- Segment - 47 - Confidence Intervals
- Segment - 48 - Determining the Appropriate Tests
- Segment - 49 - ANOVA - The Analysis of Variance
- Segment - 50 - Summary of Statistical Tests
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10
Module 9
- Module 9 - Regression
- Segment - 51 - Linear Regression and Building Models from Data
- Segment - 52 - Linear Regression Models
- Segment - 53 - Multivariate Linear Regression Models
- Segment - 54 - Data Preprocessing
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11
Labs
- Labs - Overview
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12
Quizzes
- Quiz - Overview
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13
Additional Course Readings
- Articles and downloads
- Best books on this subject
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14
Final Exam
- Final Exam: Overview and Instructions
- Final Exam: Launch here
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15
Recommended Further Readings
- Articles and Downloads
- Best books on this subject