Data Scientists take advantage of Python's powerful libraries for a variety of tasks, including:
- Data wrangling using NumPy, Pandas, and Scikit-Learn
- Data cleaning using Beautiful Soup and Regular Expressions
- Data visualization using Matplotlib, Seaborn, and Plotly
- ML using Scikit-Learn, TensorFlow, and PyTorch
- NLP using NLTK, SpaCy, and TextBlob
Free Python Data Science Resources from Accelebrate:
Why Python is The Best Language to Use for Data Science
This article explains Python's advantages for data science and why Python gives data scientists the leverage they need to perform data analysis.
Free Webinar: Python Data Science on AWS
Watch this video to learn how to scale Python data science workloads on AWS and use AWS-native tools like the SageMaker cloud machine learning platform.
What our students are saying about our Data Science with Python training:
"From a minimal Python background, this course helped me understand Python, its capabilities when analyzing data, and the tools I need to model the data in the future."
-Robert H, NASA – Kennedy Space Center
"The course was incredibly well formatted to cover a mix of theory, examples, and practice lab work. No matter your learning style, the information was covered in one shape or form. The instructor was very knowledgeable and was able to keep up the energy of a programming class over 5 days, which is no small feat!"
-Emily F, NASA – Kennedy Space Center
"This is very informative class. You will have a systematic understanding of basic Python grammar, NumPy and panda libraries and how to use machine learning algorithms provided by the sci-kit learn library. The course material covers necessary and comprehensive aspects of the topic. Also, the instructor explains the materials clearly."
-Ning S, Bank of Montreal
