Machine Learning With Python
2 Days
Overview
This course provides your analytics staff with a useful introduction to Python, teaching them how to clean, aggregate, describe, and visualize data. We impart the skills to analyse numerical, categorical, and time-series data in Python. This course is geared toward individuals who are new to Python but have basic analytical skills and some programming experience.
We will also show your team how to apply various machine learning concepts to any business problem. Your team will then be able to hit the ground running, using their new skills to immediately impact their work.
Course Outcomes
Upon completion of the course, attendees should be able to:
- Perform data analysis in Python using pandas
- Understand basic statistics needed for data analysis
- Perform a complete EDA using Python
- Understand & Apply Machine Learning Algorithms
Training Content
DAY 1: Python for Data Science and Exploratory Data Analysis
- Introduction to the Jupyter Notebook
- Python Fundamentals
- Introduction to Pandas
- Indexing & Selecting data, Slicing & Dicing
- Merging, Grouping and Summarizing Data
- Data Cleaning
- Data visualization in Python
- Introduction to Statistics
- Univariate & Bivariate Analysis
DAY 2: Supervised & Unsupervised Learning ML Algorithms
- Introduction to Machine Learning Terminology
- Introduction to Machine Learning Algorithms
- Building a Linear Regression Model in Python – with a Classic use case
- Building a Classification Model- with a Classic use case
- Unsupervised Learning Problem: Clustering- an Overview
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