Python for Data Analytics

odqxm2nkmjd
10
Feb
  • 0 (Registered)
  • (0 Review)

Python for Data Analytics is a part of our Big Data & Analytics program and is currently not being offered separately. Please visit this link CLICK HERE for the complete program details.

The lesson plan for the course is detailed in the later section. Some sample project which may be included in the class is as below:

Example Projects:

  • Draw Turtles
  • Decode Secret Code
  • Profanity Editor
  • Olympic DataSet
  • Stock Market Analysis
  • Election Analysis
  • Titanic DataSet
  • Predictive Model – Logistic Regression, Decision Tree, Random Forest
    … and more!

 

Course Curriculum

Total learning: 46 lessons Time: 3 weeks
  •   Intro to Course and Python 0/2

    • Basic Overview
    • Setup Course Resources
  •   Basics of Python for Data Analysis 0/4

    • Why Python?
    • Python 2.7 vs Python 3.4
    • Python Syntax and Programming Logic
    • Running few simple programs
  •   Python Libraries and Data Structures 0/4

    • Python Data Structures
    • Python Iterations and Conditional Constructs
    • Python Libraries
    • Few simple programs
  •   NumPy Basics: Arrays and Vectorized Computation 0/9

    • Creating ndarrays
    • Data Types for ndarrays
    • Operations between Arrays and Scalars
    • Basic Indexing and Slicing
    • Expressing Conditional Logic as Array Operations
    • Mathematical and Statistical Methods
    • Sorting
    • Linear Algebra
    • File I/O with Arrays30m
  •   Getting Started with Pandas 0/9

    • Series
    • DataFrame
    • Index Objects
    • Reindexing Dropping and Selecting Entries
    • Arithmetic and Data Alignment
    • Sorting and Ranking
    • Summarizing and Computing Descriptive Statistics
    • Handling Missing Data
    • Hierarchical Indexing
  •   Plotting and Data Visualization 0/6

    • A Brief on matplotlib
    • Line Plots
    • Bar Plots
    • Histograms and Density Plots
    • Scatter Plots
    • Plotting Maps
  •   Data Aggregation and Group Operations 0/5

    • GroupBy on DataFrames
    • GroupBy on Dict and Series
    • Aggregation
    • Splitting, Applying and Combining
    • Pivot Tables and Cross Tabulation
  •   Time Series 0/7

    • Converting between Strings and DateTime
    • Time Series Basics
    • Date Ranges, Frequencies and Shifting
    • Time Zone Handling
    • Period Arithmetic
    • Upsampling, Downsampling and Interpolation
    • Time Series Plotting

Instructors

Review

0.0

0 rating

5 stars
0%
4 stars
0%
3 stars
0%
2 stars
0%
1 star
0%