Python for Data Analytics - Module 2

  • Course Duration2 Days
  • Course StartEnrollment Monthly

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

 

Our Partners

Institutions we have partnered with or Worked with previously

MapR Technologies
Kaggle
Dataiku
Nita
Kenya Tourism Board
Barclays
British American Tobacco
Coop Bank
Craft Silicon
CRDB Bank
ICPAK
IPSOS
KAM
Lapfund
National Land Comission
NSSF Uganda
Reinsuance
Safaricom
URA