201 - Enterprise Machine Learning
Scaling advanced analysis techniques to enterprise production levels, using Amazon Web Services (AWS) and other tools to automate scripts, analysis, and report workflows to maximize your impact and minimize your workload.
We focus on the practical, not theoretical side of Data Science and Machine Learning. Our courses are tailored around teaching students how to extract insight from data using Machine Learning & AI without focusing too much on the Mathematics or mechanics behind it. Our courses are focused on practical learning with use cases and data sets from economics, social policy, ecommerce, marketing, and more. Reboot creates future economy ready employees by covering three core skill sets from the full data solutions pipeline. If you've ever been frustrated with the theoretical nature of other courses in ML and AI, then this is the course for you.
You should be proficient with the basic concepts of programming in at least one language (not necessarily Python), and should possess at least a high level familiarity with basic concepts in statistics, linear algebra, and machine learning.
Week 1 - AWS and Scaled Architecture
Production level landscape, Amazon Web Services set up, and using AWS to automate data retrieval and cleaning scripts
Week 2 - Enterprise Analysis
Creating interactive, multilayered dashboards, and scalable, production level analysis systems such as recommendation engines
Week 3 - Deep Learning
Unsupervised vs supervised learning, and how to combine unsupervised techniques with neural networks for advanced insights on raw data
Week 4 - Artificial Intelligence
Neural networks, Natural Language Processing, image recognition, and using Tensorflow for scaled 'intelligent' applications
Week 5 - Time Series and Advanced Analysis
Modeling and predicting time series such as stock prices, and combining ML techniques to optimize results
Week 6 - Enterprise Level Portfolio Project
Run an entire production level project from start to finish- use advanced ML techniques deployed on AWS' cloud based platforms to generate rich, interactive dashboards with immediately relevant insights
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Head of Analytics and Data Science