AI and Data in Business
Python for Business Data Analysis
This practical course develops directly applicable capability in Python for Business Data Analysis. Participants work in depth on Python Analytics Environment, and Working with Pandas DataFrames, and Cleaning Business Data, then convert the methods into tools and actions suited to their workplace.
Objectives
- Apply the principles and methods of python analytics environment in a workplace context.
- Apply the principles and methods of working with pandas dataframes in a workplace context.
- Apply the principles and methods of cleaning business data in a workplace context.
- Apply the principles and methods of exploratory analysis in a workplace context.
- Apply the principles and methods of visualization with python in a workplace context.
- Apply the principles and methods of reusable analysis workflow in a workplace context.
Target audience
- Professionals responsible for the subject area
- Managers and supervisors
- Analysts, coordinators, and specialists
- Project and improvement teams
- Employees preparing for broader responsibilities
Program outline
A clear structure for the learning journey.
Program outline
Outline points are grouped in one designed block instead of being treated as separate module cards.
Module 1: Python Analytics Environment
Notebooks, variables, objects, and packages
Loading CSV and spreadsheet data
Reproducible cells, comments, and file organization
Module 2: Working with Pandas DataFrames
Selecting, filtering, sorting, and renaming
Data types, missing values, and duplicates
Creating calculated business fields
Module 3: Cleaning Business Data
Standardizing dates, categories, and text
Resolving invalid and inconsistent records
Combining datasets with merge and concatenate
Module 4: Exploratory Analysis
Descriptive statistics and frequency tables
Segment comparisons and outlier review
Grouping and pivoting business measures
Module 5: Visualization with Python
Selecting appropriate chart forms
Building clear charts with labels and scales
Highlighting trends, variation, and exceptions
Module 6: Reusable Analysis Workflow
Separating inputs, transformations, and outputs
Validation checks and error handling
Exporting results and explaining analytical limitations
Materials provided
- ○ Course-specific presentation slides
- ○ Practical exercises and facilitated activities
- ○ Course-specific worksheets, checklists, and templates
- ○ Applied workplace case studies
- ○ 4D Certificate of Completion issued by 4D Training & Consultancy
- ○ Post-course support for implementation questions
Training Options
Programs can be delivered in-house, online, or in a blended format depending on your team's schedule, location, and learning objectives. When an external certificate or exam is included, certification rules and fees remain under the relevant awarding body's policies, while 4D provides the training and preparation support.
Why choose 4D
4D adapts this program to the participant group and workplace context. Delivery combines structured explanation with course-specific exercises, realistic cases, working tools, and an action-planning component so participants can transfer the learning to their roles.
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