AWS, Coursera, and DeepLearning.AI have joined hands to launch Practical Data Science, a three-course, 10-week, hands-on specialization designed for data-focused developers, scientists, and analysts familiar with Python to learn how to build, train, and deploy scalable, end-to-end ML pipelines—both automated and human-in-the-loop—in the AWS Cloud.
Each of the 10 weeks features a comprehensive, hands-on lab developed specifically for this specialization and hosted by AWS Partner Vocareum. These include:
- Foundational concepts for exploratory data analysis (EDA), automated machine learning (AutoML), and text-classification algorithms.
- How to automate a natural language processing task by building an end-to-end machine learning pipeline using BERT with Amazon SageMaker Pipelines.
- A series of performance-improvement and cost-reduction techniques to automatically tune machine learning model accuracy, compare prediction performance, and generate new training data with human intelligence.
DeepLearning.AI teamed up with an all-female team of instructors including Amazon ML Solutions Architects and Developer Advocates to develop and deliver the three-course specialization on Coursera’s education platform.
“The field of data science is constantly evolving with new tools, technologies, and methods,” says Betty Vandenbosch, Chief Content Officer at Coursera.
“Through hands-on learning, cutting-edge technology, and expert instruction, this new content will help learners acquire the latest job-relevant data science skills,” added Vandenbosch.