Training schedule
IN-COMPANY TRAINING PROGRAMS
Contact Giovanni Lanzani, if you want to know more about custom data & AI training for your teams. He’ll be happy to help you!
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Certified Data Science with Python Training
Learn the best practice in for effective data science and machine learning with this practical Python training. Explore how Python can help you take the next step in your Data & AI career, guided by GoDataDriven’s Data Science experts in this 3-days course. Earn the Data Science with Python Foundation certification after the training.
Clients we've helped
What you'll learn
Machine Learning with scikit-learn
- Machine Learning models
- Data Transformations
- Data Estimators
- How to combine these into pipelines
- How to automate everything in a grid search
- How to write building blocks
Data Visualization
- How to create plots with Matplotlib in other packages
- More advanced plots with Seaborn
- More expressive plotting libraries (e.g. plotnine, plotly or Altair)
NumPy
- Where the performance comes from
- Some limits of the performance
- About broadcasting and its advantages
- How to work with shape conventions
- The most useful NumPy functions and tricks
Jupyter Notebooks
- How to create interactive documents
- The most useful tips and tricks (magics, and more.)
- How to organize your project
Pandas
- How to perform data-wrangling tasks
- The most important methods and functions in pandas
- How to customize aggregations
- How to organize code and use pandas pipelines
- Understanding stateless transformations
- How to automate logging in pandas
The schedule
- Working with Jupyter notebooks in a sustainable way
- How to do numerical computations and linear algebra with NumPy
- Visualizing data with Matplotlib, Seaborn, and other packages
- Transforming and munging data with pandas
- ML concepts:
- Why and when to use ML
- Types of Learning tasks & ML approaches
- ML Theory:
- Optimisation with gradient descent
- Under/Overfitting, Generalisation & Regularization
- Introduction to Scikit-Learn
- Training & evaluating a Scikit-Learn estimator
- Interpreting a Scikit-Learn model
- Overview of ML algorithms
- Pros & Cons of the most common ML models
- How to choose an appropriate ML model
- Scikit-learn Pipelines
- Preprocessing with Scikit-Learn transformers
- Cross-validation and hyperparameter searches
- Hackathon
- Data Science with Python Foundation exam
Data Science with Python Foundation Certification
We have worked together with APMG International to offer you a recognized partner to get certified in Data Science.
The exam and Data Science with Python Foundation certificate are included in the course Data Science with Python. The exam can be taken directly after the training or at a moment of your choice. If you get at least 50% of the 50 multiple choice questions right, you will pass the exam and receive your certificate. More information about the exam can be found here. Prepare in advance with this Data Science with Python Foundation sample exam here. Please select “Data Science with Python Foundation” from the dropdown menu.
_ SKILL ASSESSMENT: PYTHON FOR DATA SCIENCE
Discover your knowledge level of Python for Data Science
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We believe that our courses empower people to be more effective with data and tech so they can better help colleagues and delight customers. Attending one of our training is also a great way to expand your network, increase your employability, and to command bigger salaries. If you already have a well-paying job, our prices are really affordable. Not everyone is so lucky though. So if you wish to attend one of our most popular courses, but require financial support, we'd love to hear from you.
James Hayward
Data EducatorJames holds a Master’s degree in Artificial Intelligence from the University of Amsterdam (Cum Laude); a Master’s in Educational Leadership from UCL (Merit); and a Bachelor’s degree in Mathematics from the University of Manchester (First Class Honours). He is fluent in Python and its data science libraries, such as Pandas and Sci-kit Learn, and is proficient with the deep learning frameworks PyTorch and TensorFlow.
Structured, to-the-point, good combination of theory and practical examples, very knowledgeable trainer who can explain concepts very well
It was a hands-on and tangible course. We could apply what we learned in a matter of minutes. The trainer did a great job of answering ad-hoc questions that complemented the material. We appreciated the fact that we could apply what we were taught directly to our company.
I liked every aspect of this training and would like to thank the trainers. They did an excellent job of explaining how to use Spark for data science. This is the fourth GoDataDriven training I’ve followed. All were great, but this was the best one so far.
Climbing a steep Python and Machine Learning curve in three days. This would have taken me months on my own.