Artificial intelligence
Data science and machine learning with Python
From raw data to predictive models
Five days to prepare and explore data, build and evaluate machine learning models with Python (pandas, scikit-learn) and present results that support decision-making.
- Duration
- 5 days · 35 hours
- Level
- Intermediate
- Format
- In-company · Virtual classroom
Upcoming sessions
This course is run on demand: in a virtual classroom or at your premises, on dates that suit you. Ask us for the next dates or a quote for your team.
Also available
- In-company, at your premises: France
- In a virtual classroom: France
Overview
This intensive course takes you through every step of a data science project on real datasets: preparation, visual exploration, modelling, evaluation and reporting. You learn to choose the right algorithm, avoid classic pitfalls and explain your results to non-specialists.
Objectives
- Prepare and clean data with pandas
- Explore and visualise data
- Build regression and classification models
- Evaluate and improve a model
- Present results and prepare a model for production
Who is it for?
- Analysts, management controllers, research officers
- Developers moving into data
- Engineers and scientists
Prerequisites
Basic Python (variables, loops, functions) and descriptive statistics. The "Python fundamentals" course is recommended.
Programme
Day 1
Preparing data
- Python environment and notebooks
- pandas: loading, filtering, transforming
- Missing values and outliers
Day 2
Exploring and visualising
- Descriptive statistics
- Visualisation with Matplotlib and Seaborn
- Formulating hypotheses
Day 3
Supervised learning
- Linear and logistic regression
- Decision trees and random forests
- Train / test split
Day 4
Evaluating and improving
- Metrics: precision, recall, AUC, error
- Cross-validation and hyperparameter tuning
- Unsupervised learning: clustering
Day 5
End-to-end project
- Project on a real case
- Interpreting and explaining a model
- Reporting and moving to production
Teaching method
Guided notebooks and a running project on real data. Groups of up to 10 participants, in a virtual classroom or at your premises, with a practitioner trainer. For 30 days after the course, you can email your questions to the trainer.
What you receive
- Annotated Python notebooks for every exercise
- pandas and scikit-learn cheat sheets
- Data science project methodology
Assessment and certificate
Initial assessment, hands-on exercises and a final quiz. Certificate of attendance; Onarcle certificate of achievement from a 70% score on the final quiz.
Price and funding
Public course price per participant, materials included. In-company (up to 10 participants, programme tailored to your needs): €6,990 excl. VAT per group. 10% discount from 3 participants from the same organisation. If your employer or a funding body will pay, contact us and we will find the right arrangement.
Enrolment and quotes
Book a place, request a quote or a session for your teams. We reply within 2 working days.
Software and brand names mentioned belong to their respective owners. Onarcle is an independent training provider, not affiliated with their publishers; this course does not award an official vendor certification.