Edureka Python Data Science Certification 2019

Following are the topics covered in this course:

Basic Python

• Types of variables
• Loops in Python
• Collection Datatypes
  • List
  • Tuples
  • Sets
  • Dictionaries
• Exceptional Handling
• OOPs concept
• User defined functions
• Numpy
  • Arrays
  • Matrix
• Pandas
  • Dataframes

Data PreProcessing

• Missing value Treatment
• Outlier Treatment
• Feature Scaling
• Train and Test Split

Data Visulaization

• Matplot Library
• Seaborn Library

Algorithms

Supervised Learning

• Regression
  • Simple Linear Regression
  • Multiple Linear Regression
  • Decision Tree
  • Random Forest
• Classification
  • Logistic Regression
  • K-nearest Neighbour
  • Naive Bayes
  • Support Vector Machine
  • Decision Tree
  • Random Forest

Unsupervised Learning

• Clustering
  • K-means Clustering
  • Hierarchical Clustering -Association Rule
  • Apriori Association
• Dimensionality Reduction
• Reinforcement Learning
• Time Series
  • ARIMA

Model Selection and Boosting

• K-Fold
• XGBoost