Python Training: Finance and Time Series
Python has become one of the most powerful and widely used programming tools in modern finance.
Its flexibility, extensive libraries, and ability to handle large volumes of data make it an essential skill
for financial analysts, quantitative researchers, portfolio managers, and anyone involved in data-driven finance.
This training program introduces participants to Python through practical financial applications, placing a strong
emphasis on time series analysis — a crucial aspect of financial modeling. Through hands-on lessons, students
learn how to manipulate financial datasets, perform exploratory data analysis, create visualizations, build
forecasting models, and apply machine learning techniques to real-world financial scenarios.
By the end of the course, participants will be able to construct, evaluate, and deploy financial models, develop
investment strategies based on time series data, and use Python to support rigorous, data-informed decision-making.
Introduction to Python Training: Finance and Time Series
Module 1: Introduction to Python for Finance
- Overview of Python as a programming tool for finance.
- Install and configure the Python environment with financial libraries.
- Manipulate financial data, data types, and basic operations.
Module 2: Financial Data Analysis with Pandas
- Introduction to the Pandas library for data analysis.
- Load financial data from various sources (CSV files, databases, etc.).
- Clean and preprocess data for in-depth analysis.
- Perform grouping, filtering, and statistical calculations on time series.
Module 3: Financial Data Visualization with Matplotlib and Seaborn
- Introduction to Matplotlib and Seaborn for data visualization.
- Create charts such as price curves, return histograms, and candlestick plots.
- Customize visualizations for effective presentation of financial data.
Module 4: Financial Time Series Analysis
- Understand key concepts in financial time series (volatility, trends, seasonality, etc.).
- Apply time series models such as Moving Average, Autoregression (AR), ARMA, and ARIMA.
- Evaluate and interpret model performance.
Module 5: Predicting Financial Prices with Machine Learning
- Introduction to basic machine learning and regression concepts.
- Use Machine Learning libraries such as Scikit-Learn to predict financial prices.
- Compare regression model performance to achieve accurate predictions.
Module 6: Practical Finance Applications with Python
- Apply acquired skills to solve real-world financial problems.
- Create investment strategies using financial time series analysis.
- Implement risk and portfolio analysis to support informed decision-making.
Other course(s) in this category
→ Statistics and Data Analysis Training with SPSS
→ Python Training: Finance and Time Series
Prerequisites:
Objectives:
- Acquire the skills needed to use Python for finance and time series analysis.
- Master financial data manipulation using the Pandas library and perform analytical operations.
- Learn how to visualize financial data with Matplotlib and Seaborn for improved interpretation of trends and patterns.
- Be able to apply modeling techniques — including time series models and machine learning — to predict financial prices and develop informed investment strategies.
Online
- 12/03/2026
- 13/03/2026
- 11/06/2026
- 12/06/2026
- 23/07/2026
- 24/07/2026
Pricing
Practical information
- Duration: 2 day(s)
- Schedule: 9:00 a.m. to 4:30 p.m. (2 coffee breaks + 1-hour lunch)
-
Format:
- Online (live virtual classroom)
- Or in person, depending on availability
📄 Download course outline (PDF)
Registration detailsInterested in this training?
Free quote with no obligation
Registration with credit card payment
FR
« Je tiens à vous remercier tous les deux d’avoir offert à mes ressources une excellente formation COBOL au cours des trois derniers jours.
Mamadou, merci d’avoir été si accommodant malgré le court préavis et d’avoir envoyé votre formateur à Gatineau pour ce cours personnalisé.
Nous avons hâte de poursuivre notre collaboration pour de futurs besoins de formation. »
(Traduit de l’anglais)
EN
“I want to thank you both for providing my resources with excellent COBOL training over the past 3 days. Mamadou, thank you for being so accommodating on such short notice and for sending your facilitator to Gatineau for this customized and personalized training course. We look forward to continuing our partnership for future training needs.”
FR
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EN
“Mamadou helped us reorganize our stop panel using a reporting tool, Crystal Reports. He successfully delivered precise, pixel-perfect work,
as we needed a report that matched the original graphic design. He helped us break the project down into cycles and integrate the report
into our corporate software. What we appreciated most was his attention to detail and consistency. Mamadou was very professional and
is knowledgeable in many other technologies. Thank you.”
(Translated from French)
FR
« Ce fut un plaisir de faire affaires avec Doussou Formation. Ce qui fait LA différence est le service personnalisé totalement à l'écoute des participants ainsi que l'adaptation aux besoins de formation. Flexibilité / Adaptabilité / Professionnalisme / Courtoisie. Merci ! »
EN
“It was a pleasure doing business with Doussou Formation. What truly makes THE difference is the personalized service, fully attentive
to participants, as well as the ability to adapt the training to their needs. Flexibility / Adaptability / Professionalism / Courtesy. Thank you!”
(Translated from French)