E-Learning
Fully online225,-
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- Wherever you want
- Whenever you want
- At your own pace
In this e-learning course you dive into data analysis with Python and JupyterLab. You work with NumPy, pandas and Matplotlib to edit, group and visualise data intelligently. A year of access, at your own pace.
Description
In this e-learning course you get to work with Python for data analysis via JupyterLab. Python is a versatile programming language with clearly readable code, allowing you to achieve a great deal with few lines. Thanks to its intuitive set-up and the use of indentation, Python is accessible and is used worldwide for scripts, applications, data analysis and websites.
You work in JupyterLab with Jupyter notebooks and learn how to write, test and share Python programs quickly. You go into NumPy in more depth for working with one-dimensional and two-dimensional arrays, and into pandas for segmenting and grouping data using Series objects and DataFrames. You also gain insight into simple visualisation techniques with Matplotlib.
The course is in English and consists of videos, lectures, quizzes and exercises. You will spend approximately 16 hours on the material. A basic knowledge of Python is required: you can work with lists, tuples and dictionaries, with loops and conditionals, and you can write your own functions. Once activated, you have access to the e-learning course for a year, so you can work at your own pace.
Topics
In this e-learning you work in JupyterLab on data analysis with Python. You use Jupyter notebooks and Markdown to record your code and explanations clearly. After that you dive into the most important libraries for data analysis and visualisation.
- working with JupyterLab and Jupyter notebooks
- documenting with Markdown
- the purpose and use of NumPy
- one-dimensional NumPy arrays
- two-dimensional NumPy arrays
- using Boolean arrays to create new arrays
- the purpose and application of pandas
- Series objects for one-dimensional data
- DataFrame objects for two-dimensional data
- creating plots with Matplotlib
Result
After this e-learning course you will work independently with Jupyter Notebook to write, test and share Python programs. You use NumPy for calculations with arrays and Pandas for segmenting and grouping data. You also create clear visualisations with Matplotlib and use all of this for clear data analyses.
Target audience
This e-learning course is intended for data analysts, researchers, developers and students who want to take their data analysis to a higher level with Python and JupyterLab. You already have a basic knowledge of Python: you can handle lists, tuples and dictionaries, you write loops and conditionals and you can create your own functions. The course is in English, so you need to be comfortable reading and listening in English.
Teaching method
You follow this course as an e-learning course, entirely at your own pace. You get access to extensive videos, lectures, quizzes and practical exercises. This takes you step by step towards carrying out data analyses independently with Python and JupyterLab.
Allow for around 16 hours of study time. The course remains available for a year after activation, so you can always go back to sections you would like to review. The course is delivered in English.
Prior knowledge
You need basic knowledge of Python. You can work with lists, tuples and dictionaries, you understand loops and conditionals and you can write your own functions. No further prior knowledge is required.
Comments
This e-learning course is in English and remains accessible for a year after activation. You work through videos, quizzes and exercises at your own pace. Basic knowledge of Python (lists, tuples, dictionaries, loops, conditionals and functions) is required to keep up.
In-company
Would you like to organise this training for a whole group or several groups? This can be cost-effective. For example, we can tailor the content entirely to your organisation, and training a whole group is also cheaper.
Are you looking at large numbers of participants or a complete academy? That involves a great deal. Consider planning and communication, for example, or identifying and agreeing the objectives and content of the training. Or differences in level, feedback mechanisms and safeguarding. Fortunately, Learnit has extensive experience in this field (more than 25 years) and we are happy to help you through this process.
