Python Fundamentals for Business Analysts

Data analysts

This programme introduces students to the programming language Python and its use for programming and analytics.
Through a hands-on data science project, students will learn how to program in Python and how to use Python libraries relevant to data analytics such as pandas, matplotlib and seaborn, which provide powerful tools for creating detailed and comprehensive visualisations.
Business analyst can utilise Python’s capabilities in statistical analysis, predictive modelling, machine learning and drive business strategies and decision making.

The aim of the course are

• To introduce students to object-oriented programming  and Python as generic programming language
• To train students in Python libraries relevant to data analytics such as pandas, matlplotlib, NumPy and seaborn

Outlines

• Know what data science is
• Introduction to python basics (data types, loops, conditionals and functions)
• Data structures in Python
• Working with data in Python
• Python libraries for business analysis (pandas)
• Data visualization with Python (matplotlib, seaborn)
• Apply your data science skills to a real-life data set and present your project to peers

• Get introduced to programming in general and in particular in Python
• Know its applications in data analysis and business analysis
• Learn how to use notebooks like Jupyter or Google Colab
• Write and execute Python programs that involves conditional and loop statements
• Analyse and visualise data using Pandas
• Know how to work with flat files and interact with SQL databases
• Prepare and visualise data using Matplotlib and Seaborn
• Analyse time series and price options using stochastic models

Part 1: Introduction to Python and Programming Concepts (12 hours)

• Introduction
• Python Data Types and Variables
• Control Structures
• Python Functions
• Python Libraries, Modules and Virtual envs
• File Handling and Exceptions in Python

Part 2: Data Analysis and Visualization with Python Libraries (8 hours)

• Python Libraries for Data Analysis - Numpy and Pandas
• Manipulating DataFrames
• Selecting and Filtering Data
• Data preparation and cleaning
• Data Transformation
• Grouping and Aggregation

Data Visualization with Matplotlib and Seaborn (4 hours)

Part 3: Python real-life application (4 hours)

• Working with flat files and SQL Databases (2 hours)
• Time Series Analysis and Stochastic Models (4 hours)

Conclusion:

• Recap of the course content
• Real-life applications of Python for business analysts
• Further resources for learning and improving Python skills
• Open discussion and final thoughts

Attestation, Certificat:

At the end of the training, a certificate of attendance will be available either on your client account or on demand at the customer service.
Candidates who successfully complete the examination will receive the following certificate of completion: "Certified Business Analyst with Python"

Autres informations:

Online exam