Duration
3 days
Overview
Python is a programming language that may be utilized for a wide variety of purposes, from simple user scripts to complex APIs and web servers. It has a simple, highly readable syntax which makes it a suitable language for those who want to know the best way to write applications.
This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science! This course is truly step-by-step. In every new lecture we build on what had already learned and move one extra step forward. End of the course we will have a capstone project, where we can truly experience how all learning on python we can use to solve real world problem.
Course Outline
Introduction to the Course
- Environment Set-Up
- Python Environment Setup
- Jupyter Overview
- Jupyter Notebooks
Python Crash Course
- Introduction to Python Crash Course (Includes variable, loop, conditional statement etc. from scratch)
- Python Crash Course Exercises
Python for Data Analysis - Pandas
- Introduction to Pandas
- Series
- DataFrames
- Missing Data
- Groupby
- Merging Joining and Concatenating
- Operations
- Data Input and Output
- Pandas Exercises
Python for Data Visualization - Seaborn
- Introduction to Seaborn
- Distribution Plots
- Categorical Plots
- Matrix Plots
- Grids
- Regression Plots
- Style and Color
- Seaborn Exercise
Introduction to Machine Learning
- Supervised Learning Overview
- Evaluating Performance - Classification Error Metrics
- Evaluating Performance - Regression Error Metrics
- Machine Learning with Python
Capstone Project in Python
Programme scope, delivery arrangements and suitability are confirmed during enquiry.