This course teaches you to collect, clean, and analyze data with Python using data science libraries.
Collect different types of data.
Clean data using the Pandas and NumPy libraries.
Visualise data using the Matplotlib, Seaborn, etc. libraries.
Perform descriptive and multivariate statistics, regressions.
Create dashboards, etc.
Python:
- Python refresher
- Refresher on descriptive statistics
Data science libraries 1:
- Data manipulation with the pandas and numpy libraries
- Data types
- Tools for loading data
- Describe and transform data
- Describe and transform unstructured data
- Time series data processing
- Extract descriptive statistics
Data science libraries 2:
- Data visualisation with Matplotlib and Seaborn
- Scatter plot
- Building histograms, bar charts, etc.
- Animated charts
- Installing and using Cartopy (mapping)
- Interactive charts
- Scrape data from a web page
- Dashboard creation
Handling missing data:
- Causes of missing data
- Identify and handle missing data
Introduction to Machine Learning:
- Linear regression
- Logistic regression
Practical exercises.
Data analysis project.
This course takes place in three stages:
Presentation of concepts,Examples and practical exercises (data analysis),Exercises and quizzes – correction of exercises.
20% theory and 80% practice.
Complete a project covering all the tools addressed during the course.
Issuance of a certificate of attendance.
Address: Color Business Center, 19 rue de l’industrie L-6089 Bertrange
For in-company training, please contact us.
