Advanced Python Programming Outlines

Topics: OOP programming, Data Analysis, Machine Learning, Backend Developing

session1 

OOP basics: Objects, Classes and Inheritance

session2

Polymorphism, Encapsulation and Data Abstraction

session3

Numpy and start of Pandas

 Libraries: Numpy & Pandas

 Learning about how different mathematical operations can be done via Numpy

 Learning about Pandas, concept of data and data frame and etc.

Session 4

More about Pandas and Data visualization

Libraries: Pandas, Seaborn & Matplotlib

 Data Analysis and querying data with Pandas

Drawing different charts and graphs with Seaborn and Matplotlib

Session 5

Exploratory Data Analysis on a real-world Data

Mini project: Working on a real-world Data from Kaggle.

Session 6

What is AI and what are the different parts of it. (Talking about search, logic, agent, ML and DL)

Theorical Session

Session 7Linear Regression algorithm (Sickit Learn, Correlation, One-Hot encoding and etc.)

 Libraries: Sickit Learn, Pandas, Numpy, Seaborn and Matplotlib

 Data from Kaggle

Session 8

Logistic Regression and KNN for classification

 Libraries: Sickit Learn, Pandas, Numpy, Seaborn and Matplotlib

 Data from Kaggle

Session 9

Decision Tree and Mini Project

 Libraries: Sickit Learn, Pandas, Numpy, Seaborn and Matplotlib

 Mini project: Students are provided with a dataset and must choose the best Machine Learning algorithm to use.

Session 10

Intro to backend development. What is API? What is HTTP and more

 Theorical Session

Session 11

Starting with FastAPI. Write a RESTful API using FastAPI and testing it using swagger.

 Libraries: FastAPI & Uvicorn

Session 12

What is a Database? Talking about SQL databases and some query languages.

 Theorical Session

Session 13

Writing some RESTful APIs in FastAPI with database included.

•Libraries: FastAPI and dependent libraries for Database handling

Session 14- 15 and 16

Final Project: Let’s put all of the things we have learnt so far together!

Final Grade: