Python Training

Data is the new crude oil. And business success in the 21st century is heavily reliant on the ability to mine and use relevant data about consumers, internal operations, financial operations and industry trends to drive business decisions.

Remoik Data & Analysis, Nigeria’s leading business data analysis company is putting together this special training for proactive business professionals who already have some experience with business reporting and quantitative data analysis.

We will be focusing on building analysis models with Python. Python has the advantage of being a full-fledged programming language so the knowledge you will gain from this training will go beyond writing scripts to analyze data. We will provide you all the software and materials needed.

Remoik Data & Analysis, Nigeria’s leading business data analysis company is putting together this special training for proactive business professionals who already have some experience with business reporting and quantitative data analysis. The participants must be comfortable with being taught to write programs (coding) as the curriculum is more of a specialized programming class with business case.

If you are completely new to Python, we advise you take an hour or 2 to go through the attached official intro to Python (provided to all who send us email inquiry). Just scanning through will help you be familiar enough to get the most out of the hands-on class.

This training is focused on building analysis models with Python. Python has the advantage of being a full-fledged programming language so the knowledge you will gain from this training will go beyond writing scripts to analyze data. We will also provide you all the software setup and data/scenarios needed.

Python for Data Analysis Training Outline:

1) Understanding Python programming language

  1. Installing and setting up Python
  2. Introduction to Anaconda
  3. Python program flow
  4. List Comprehension
  5. Dictionary Comprehension
  6. String Comprehension
  7. Basic Statistics

 

2) Python for Data Analysis

  1. NumPy
  2. Pandas
  3. SciPy and Scikit-learn
  4. Matplotlib
  5. Using IDEs
  6. Different machine learning algorithms

 

3) Practical Projects

  1. Project 1: Analyzing Nigeria stocks and economic data
  2. Project 2: Analyzing Social Media data
  3. Project 3: Churn analysis
  4. Project 4: Market Basket Analysis
  5. Project 5: Web scrapping

 

4) Weekly Assignments (spread over 4 weeks)

  1. Week 1 assignment project
  2. Week 2 assignment project
  3. Week 3 assignment project
  4. Week 4 assignment project