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.
Outline points are grouped in one designed block instead of being treated as separate module cards.
01Python Analytics Environment3 topics
- Notebooks, variables, objects, and packages
- Loading CSV and spreadsheet data
- Reproducible cells, comments, and file organization
02Working with Pandas DataFrames3 topics
- Selecting, filtering, sorting, and renaming
- Data types, missing values, and duplicates
- Creating calculated business fields
03Cleaning Business Data3 topics
- Standardizing dates, categories, and text
- Resolving invalid and inconsistent records
- Combining datasets with merge and concatenate
04Exploratory Analysis3 topics
- Descriptive statistics and frequency tables
- Segment comparisons and outlier review
- Grouping and pivoting business measures
05Visualization with Python3 topics
- Selecting appropriate chart forms
- Building clear charts with labels and scales
- Highlighting trends, variation, and exceptions
06Reusable Analysis Workflow3 topics
- 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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