Python for Data Analytics - Module 2

Description

Course Description:

Python is becoming more and more popular for doing data science. Companies worldwide are using Python to harvest insights from their data and get a competitive edge. This course will cover the opportunities available for the telecommunication company to leverage python in order to make data analysis that fuel driven decisions. 

Learning Outcomes:

By the end of this course, you should be able to:

• Explore Python language fundamentals, including basic syntax, variables, and types
• Build Numpy arrays, and perform interesting calculations
• Supercharge your scripts with control flow, and get to know the Pandas DataFrame
• Be able to quantitatively define an answerable, actionable question
• Understand the difference between machine learning and frequentist approaches to statistics
• Implement classification and regression models using machine learning
• Score new datasets, evaluate model fit, and quantify variable importance

Key Objectives:

• Learn to use NumPy for Numerical Data
• Learn to use Pandas for Data Analysis
• Visualise data using python liblaries
• Implement Machine Learning Algorithms

Course Outline:

Module 1: Introductory Steps

Module 2: Data Science in Python

Module 3: Visualization

Module 4: Machine Learning Introduction

Module 5: Advanced Machine Learning