Who is this training for?
Data analysts, Python developers interested in majoring in data analytics.
Training objectives
- Prepare data for analysis (data aggregation, data normalization).
- Analyze and interpret data.
- Visualize data and present analysis results.
- Assist in decision-making, with a view to improving the company's strategy.
- Correct any problems in the processing chain.
Summary
Master data preparation, analysis, and visualization with Python. This training will allow you to aggregate and standardize data, analyze and interpret results, visualize your data and present your analysis results to help in decision-making and improve business strategy.
Course outline
Introduction
- Preparing Data for Analysis (Common Issues, Missing Data) Data Analysis
- Key Metrics • Comparison Analysis
- Trend Analysis • Ranking Analysis
- Analysis of Variance
- Contribution Analysis
- Frequency Analysis
- Correlation Analysis
- Pareto Analysis
Approach and methodology
This course emphasizes a practical, applied approach, combining focused conceptual lectures with data analysis exercises done with Python. Learning is centered on the manipulation of real datasets, in order to develop the ability to prepare, analyze and interpret data independently. Structured progression promotes the gradual development of visualization and results communication skills to support decision-making.
Recommendations
Have an ease in programming in Python, notions of descriptive statistics. Basic knowledge of Python programming Basic knowledge of descriptive statistics Fluency with data manipulation (Excel, CSV, etc.) Understanding of the concepts of data analysis and interpretation
