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Python is a high level dynamic programming language. Using python, programming becomes more simpler as it requires just few lines to code. By taking this course one will have some basic knowledge about Python Programming.

  • Contents
    • What is Python & History
    • Installing Python & Python Environment
    • Basic commands in Python
    • Data Types and Operations
    • Python packages
    • My first python program
    • If-then-else statement
    • Data importing and exporting
    • Working with datasets
    • Creating new variables
    • Taking a random sample from data
    • Descriptive statistics
    • Quartiles, Percentiles
    • Box Plots and Graphs
  • After completion of this course, one will have good knowledge on python installation, data handing, basic Python commands, etc.

Course Curriculum

Session 1 - Introduction to Python
Handout – Introduction to Python 00:00:00
1.1 Python Intoduction and IDE FREE 00:00:00
1.2 Basic Commands in Python FREE 00:00:00
1.3 Objects, Number and Strings 00:00:00
1.4 Objects, List, Tuples and Dictionaries 00:00:00
1.5 If_else and For_loop 00:00:00
1.6 Functions and Packages 00:00:00
1.7 Important Packages 00:00:00
1.8 End Note 00:00:00
Python Quiz Unit 1 Unlimited
Session 2 - Data Handling in Python
Handout – Data Handling in Python 00:00:00
2.1 Introduciton to DataHandling FREE 00:00:00
2.2 Basic Commands and Checklist FREE 00:00:00
2.3 Subsetting the Dataset 00:00:00
2.4 Calculated Field Sort Duplicates 00:00:00
2.5 Merge and Exporting 00:00:00
Python Quiz Unit 2 Unlimited
Session 3 - Basic Statistics, Graphs and Reports in Python
Handout – Basic Statistics, Graphs and Reports in Python 00:00:00
3.1 Basic Statistics and Sampling FREE 00:00:00
3.2 Discriptive Statistics 00:00:00
3.3 Percentile and Boxplot 00:00:00
3.4 Graphs Plots and Conclusion 00:00:00
Python Quiz Unit 3 Unlimited
Session 4 - Data Cleaning and Treatement
Handout – Data Cleaning and Treatement 00:00:00
4.1 Data Cleaning Intro and Model Building Cycle FREE 00:00:00
4.2 Model Building Cycle FREE 00:00:00
4.3 Data Cleaning Case Study 00:00:00
4.4 Step1 Basic Content of Dataset 00:00:00
4.5 Variable Level Exploration Catagorical 00:00:00
4.6 Reading Data Dictionary 00:00:00
4.7 LAB – Step2 Catagorical Variable Exploration 00:00:00
4.8 Step3 Variable Level Exploration – Continuous 00:00:00
4.8.1 LAB – Step3 Variable Level Exploration 00:00:00
4.9 Data Cleaning and Treatments 00:00:00
4.10 Step4 Treatment – Scenario1 00:00:00
4.10.1 LAB – step4 Treatment – scenario 1 00:00:00
4.11 Step4 Treatment – Scenario2 00:00:00
4.11.1 LAB – step4 Treatment – scenario 2 00:00:00
4.12 Data Cleaning – Scenario 3 00:00:00
4.12.1 LAB – Data Cleaning – Scenario 3 00:00:00
4.13 Some Other Variables 00:00:00
4.14 Conclusion 00:00:00

Course Reviews

5

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  1. Profile photo of Chandan Kumar Gupta

    Overall

    5

    Overall good to build an interest in data analytics areas. I learned something new out of it.because it is mixture of theories and practical as well. It covered some libraries like numpy, pandas, matplotlib, and various plots like Bar, scatter graph, boxed graph.
    In short : simple, in own language with subtitle, easy to understand…!