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Data Science Course Outline

Predictive Analytics and Machine Learning with Python

Intro to Data Science What is Data Science
Roles and Responsibilities of a Data Scientist
Life cycle of Data Science project
Tools and Technologies used
Statistics Fundamentals of Mathematics and Probability
Sampling Theory
Descriptive Statistics
Inferential Statistics
Python Programming Types of Operators
Data Types
Flow Controls
List Compressors
Numpy Library for Data Analysis
Pandas Library for Data Analysis
Data Visualization with Python Matplotlib library
Seaborn library
Pandas Built-in data Visualization

Data handling and Data Manipulations with Pandas

Data Pre-processing Sanity Checks
Missing value detection and treatment
Outliers detection and treatment
Variable transformation techniques
Exploratory data analysis
Uni-variate & Bi-variate analysis
Machine Learning Algorithms Supervised Learning Algorithms
Linear Regression
Logistic Regression
Decision Tree and Random Forest
Support Vector Machine
Naïve Bayes
Unsupervised Learning Algorithms
K Means Clustering
Hierarchical Clustering
Dimensionality Reduction PCA – Principal Component Analysis
LDA – Linear Discriminant Analysis
Other Topics XG Boosting
K-fold cross validation
Stratified cross-validation