SYLLABUS:

Module 1 : Python Language Fundamentals

Basic Data Types and Operations : About 5 to 8 hours

• Numbers
• Strings
• List
• Tuple
• Dictionary
• Set
• Loops

• If - else construct
• While and For Loops
• Break and continue

Module 2 : Working with Data

Data Manipulation : 3 to 5 hours

• Numpy
• Pandas
• Series and DataFrames
• Scikit Learn package
• Working with missing data
• Usage of GroupBy
• Merging â?? Joining
• Concatenation
• Plotting Data with various plots

Module 3 : Statistics and Math

• Binomial Theorem
• Types of Distribution

Normal Distribution

Right Skewed Distribution

• Standard Deviation
• Hypothesis Testing

Module 4 : Introduction to Machine Learning

Types of Learning

• Supervised
• Un Supervised

Module 5 : Working with Machine Learning Models

• Supervised Learning - Regression
  • Linear Regression
  • Multiple Regression

• Supervised Learning - Classification
  • Logistic Regression
  • Decision Trees
  • Random Forrest
  • SVM

• Un Supervised Learning
• Clustering
  • Hierarchical
  • K Means

• Model creation
• Evaluation of Model
• Evaluation Metrics
• Fine tuning the model