Junior Data Scientists looking to expand into cloud-based Machine Learning concepts on AWS and GCP.

Business and analytics professionals with some SQL experience looking to move to the next generation of Data Science.

Covers Python and Google Cloud Platform.

Walks through EDA (exploratory data analysis).

Teaches how to develop a Data Engineering API with Flask and Pandas.

Introduces Data Science concepts and Python fundamentals for Machine Learning.

He is the founder of Pragmatic AI Labs, a training, consulting, and AI/ML product company that specializes in cloud native Machine Learning and AI Solutions. In the past ten years, he has been responsible for shipping many new products at multiple companies that generated millions of dollars of revenue and had global scale. This experience has been with a wide variety of companies including ABC, Caltech, Sony Imageworks, Disney Feature Animation, Weta Digital, AT&T, Turner Studios, and Linden Lab.

He has worked in roles ranging from CTO, General Manager, Consulting CTO and Cloud Architect. Professionally, Noah has approximately 20 years of experience of programming in Python and is a member of the Python Software Foundation. He has an MBA from UC Davis, an MS in Computer Information Systems from Cal State Los Angeles, and a BS in Nutritional Science from Cal Poly San Luis Obispo. He is also a certified AWS Solutions Architect and an SME (Subject Matter Expert for Machine Learning for AWS). He has published close to 100 technical publications, including two books on subjects ranging from Cloud Machine Learning to DevOps. He is teaching graduate machine learning and consulting on Machine Learning and Cloud Architecture for students and faculty. Noah Gift is lecturer and consultant at UC Davis Graduate School of Management in the MSBA program. The supporting code for this LiveLesson is located at. Software engineering fundamentals tie the series together, with key instruction on linting, testing, command-line tools, data engineering APIs, and more. Noah Gift covers how to get started with Python via Jupyter Notebook, and then proceeds to dive into nuts and bolts of Data Science libraries in Python, including Pandas, Seaborn, scikit-learn, and TensorFlow.ĮDA, or exploratory data analysis, is at the heart of the Machine Learning therefore, this series also highlights how to perform EDA in Python and Jupyter Notebook. This 8-hour LiveLesson video course shows how AWS and Google Cloud Platform can be used to solve real-world business problems in Machine Learning and AI.

Learn just the essentials of Python-based Machine Learning on AWS and Google Cloud Platform with Jupyter Notebook. Video description 8+ Hours of Video Instruction

Learn python jupyter notebook