Fundamentals of Data Science & Machine Learning with Python

Learn Data Science, Probability & Statistics, Python, Data Gathering & Cleaning, Machine Learning & Data Visualization

What you’ll learn

Become a well round Data Scientist
Python Programming for Data Science
Complete working flow of Data Science project
Role of Data Scientist in Today’s World
How to apply Probability concepts to Solve real life problems
Collecting Data from API (Application Programming Interface)
Collecting Data from JSON
Collecting Data from Local file, and CSV and Excel
Learn different techniques to clean the data
Probability for Data Science – Probability definition, Random Variables, Probability Distribution, Bayes’ Theorem
Discrete and Continuous Probability Distribution
Basic Statistical Concepts for Data Science
Learn about Collections in Python
What is Machine Learning and its types
Machine Learning Models – Simple and Multiple Linear Regression, Advance Linear Regression, Decision Tree, SVM, K-means Clustering
Supervised and Unsupervised machine learning models
Learn to use the popular library Scikit-learn in your projects
Learn to perform Classification and Regression modelling
Probability Distributions – Binomial Distribution, Normal Distribution and Poisson Distribution
Statistical Concepts – Mean, Mode, Median and Standard Deviation
Data Visualization