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Introduction Python (EN)
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Do you want to learn how to program in Python? And do you want to know how Python can help you get insights from your data and what you can do with these insights?
Training codeCGAPYTINCESpoken LanguageEnglishLanguage MaterialsEnglishDayparts4Price€1.600,00excl. VAT No extra costs.Book Introduction Python (EN) now
In group training, we use several learning methods to help you obtain the knowledge, give you helpful insights and get you inspired. Check the Spoken language and Language materials on the left for language info.
What is Introduction Python
This training is designed for those who want to learn how to program in Python and understand how Python can help them get insights from their data. The ‘Introduction to Python’ training provides you with the tools to develop yourself as a Data Analyst / Data Scientist by learning to clean, prepare, analyse, and present data with Python. Topics covered include Python basics, working with Jupyter Notebooks, programming concepts, data cleaning, data analysis, data presentation, and specific modules like Numpy, Pandas, and Plotly. The training combines theoretical principles of Python with practical examples, giving you the opportunity to gain hands-on experience with Python.
Python, with its versatility and wide-ranging applications across various fields, particularly data analysis, serves as a powerful tool in the modern digital world. Our trainers, armed with their extensive knowledge and practical experience, breathe life into theoretical concepts, offering insights drawn from real-world applications and industry best practices. This fusion of theory and practice not only enriches the learning journey but also equips learners with skills that are directly applicable in real-world scenarios.
Who should attend Introduction Python
- Data Analysts: Professionals who want to leverage Python for data analysis.
- Data Scientists: Individuals looking to enhance their data manipulation and analysis skills.
- Data Engineers and Software Engineers: Professionals who want to integrate Python into their development process.
Prerequisites
Beginning skills and general knowledge of data analysis. The 'Introduction to Data Analysis' training addresses these topics and is ideally suited to follow as a training prior to this.
During this training you need a laptop on which you can install software: Anaconda (https://www.anaconda.com/products/individual).Objectives
At the end of the training, you will be able to:
- Understand what Python is and how to start using it.
- Use Python to clean, prepare, analyse, and present your data.
This training is designed to provide a comprehensive introduction to Python, making it ideal for anyone looking to learn this powerful programming language.
Do you want to learn how to program in Python? And do you want to know how Python can help you get insights from your data and what you can do with these insights?
Training codeCGAPYTINCESpoken LanguageEnglishLanguage MaterialsEnglishDayparts4Price€1.600,00excl. VAT No extra costs.With an Incompany training you have several advantages:
- You choose the location
- You experience the training with your colleagues, so it is always in line with your practice
- The trainer can tailor explanations, examples and assignments to your organization
- In consultation exercises can be adapted to organization-specific questions
Request more information or a quote.What is Introduction Python
This training is designed for those who want to learn how to program in Python and understand how Python can help them get insights from their data. The ‘Introduction to Python’ training provides you with the tools to develop yourself as a Data Analyst / Data Scientist by learning to clean, prepare, analyse, and present data with Python. Topics covered include Python basics, working with Jupyter Notebooks, programming concepts, data cleaning, data analysis, data presentation, and specific modules like Numpy, Pandas, and Plotly. The training combines theoretical principles of Python with practical examples, giving you the opportunity to gain hands-on experience with Python.
Python, with its versatility and wide-ranging applications across various fields, particularly data analysis, serves as a powerful tool in the modern digital world. Our trainers, armed with their extensive knowledge and practical experience, breathe life into theoretical concepts, offering insights drawn from real-world applications and industry best practices. This fusion of theory and practice not only enriches the learning journey but also equips learners with skills that are directly applicable in real-world scenarios.
Who should attend Introduction Python
- Data Analysts: Professionals who want to leverage Python for data analysis.
- Data Scientists: Individuals looking to enhance their data manipulation and analysis skills.
- Data Engineers and Software Engineers: Professionals who want to integrate Python into their development process.
Prerequisites
Beginning skills and general knowledge of data analysis. The 'Introduction to Data Analysis' training addresses these topics and is ideally suited to follow as a training prior to this.
During this training you need a laptop on which you can install software: Anaconda (https://www.anaconda.com/products/individual).Objectives
At the end of the training, you will be able to:
- Understand what Python is and how to start using it.
- Use Python to clean, prepare, analyse, and present your data.
This training is designed to provide a comprehensive introduction to Python, making it ideal for anyone looking to learn this powerful programming language.
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e-CF competences with this course
At Capgemini Academy we believe in transparency and clarity in the training landscape. That is why, in the table below, we show you to which e-CF competence this training or certification contributes. For more information about how to use the e-Competence Framework read more here. If you want to know how you can apply the e-CF within your organization, read more on this page.
e-Competence Level | 1 | 2 | 3 | 4 | 5 |
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D.10.Information and Knowledge Management | |||||
B.1.Application Development | |||||
E.1.Forecast Development | |||||
A.6.Application Design |