Follow the below training pathway to build your understanding of Data Science. The practical examples will be based on Python programming language:

• What is machine learning?

Feature Engineering

• Missing Data Imputation
• Categorical Variables Encoding
• Handling Outliers
• Feature Scaling

Dimensionality Reduction

• Principal Component Analysis (PCA)
• Linear Discriminant Analysis (LDA)

Clustering

• K-Means Clustering
• Agglomerative (Hierarchical) Clustering

Classification

• Support Vector Machines (SVM)

General

• Gridsearch

Deep Learning

• Deep Learning at Scale