Data-Science-with-Python
Course Outline
- Intoduction to Python
- What and Why Python?
- Python Basic Instructions
- Data Types
- Operators
- Control Structures
- Functions and Packages
- Basic Data Science Tools in Python
- Lists
- Matplotlib
- Dictionaries & Pandas
- Manuplating data
- Advance Python
- Functions
- Filling
- Object Oriented Programming
- Importing Data in Python
- Import Data from Files
- Import Data from SQL Databases
- Import Data using APIs
- Cleaning Data in Python
- Clean Data using SOAP
- Introduction to Databases
- SQL Databases
- NoSQL Databases
- SQL Queries
- Creating and Manipulating your own Databases
- Intoduction Data Visualization
- Customizing plots
- Plotting 2D arrays
- Statistical plots with Seaborn
- Analyzing time series and images
- Statistical Methods in Python
- Graphical exploratory data analysis
- Quantitative exploratory data analysis
- Thinking probabilistically
- Parameter estimation
- Hypothesis testing
- Machine Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Deep Learning
- Neural Networks
- Building Deep Learning Models
- Optimizing Deep Learning Models
Books
- Starting Out with Python
- Data Science from Scratch, by Joel Grus
- Data Science For Dummies, by Lillian Pierson
- Machine Learning Yearning, by Andrew Ng
- Think Stats: Probability and Statistics for Programmers, by Allen B. Downey
References
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