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Week 1-2
Insight by Industry Leaders and Introduction to Python and Python Libraries
Designed to help learners decode the mystery of artificial intelligence and its business applications, this introductory AI course provides an overview of concepts and workflows, machine learning and deep learning, and performance metrics.
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Week 3-4
Introduction to Machine Learning
This practical course targets individuals who have introductory-level Python programming experience. The course will prepare students to apply efficient, well-known mining models to make sense of data using Python, one of the most popular programming languages among data scientists. Topics include data visualization, feature importance and selection, dimensionality reduction, clustering, and classification. All data sets used in this course are gathered as live-data or inspired by real-world domains that can benefit from machine learning.
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Week 5-6
First Models and Tests
Explore the concepts of machine learning and understand how it’s transforming the digital world. Covering an exciting branch of artificial intelligence, this course will provide the skills you need to become a machine learning engineer and unlock the power of this emerging field.
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Week 7-8
Common Machine Learning Models
This course focuses on the key mathematical concepts students will encounter in the study of machine learning and is designed to reinforce key concepts students have learned previously. While not intended as a full, foundational math curriculum, this course will serve as a refresher for students who have not recently studied math.
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Week 9-10
Neural Networks 1
Designed for the future of programming, this course covers the primary disruptors in the tech industry: machine learning and Python. This course will equip students with an understanding of the scope and application of machine learning, Python, complex logic and data structures, and machine learning processing.
This deep learning course with TensorFlow certification training is developed by industry leaders and aligned with the latest best practices. You’ll master deep learning concepts and models using Keras and TensorFlow frameworks, and implement deep learning algorithms, preparing you for a career as deep learning engineer.
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Week 11-12
Neural Networks 2
This course focuses on the key mathematical concepts students will encounter in the study of machine learning and is designed to reinforce key concepts students have learned previously. While not intended as a full, foundational math curriculum, this course will serve as a refresher for students who have not recently studied math.
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Week 13-14
Natural Language Processing
The Natural Language Processing module covers concepts like statistical machine translation and neural models, deep semantic similarity models (DSSM), neural knowledge base embedding, deep reinforcement learning techniques, and more.
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Week 15-16
AWS – SQL for Machine Learning
The course will cover the foundations of cloud computing and databases using AWS & SQL. This course will prepare students to deploy their machine learning models in a real-world context.
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Week 17-19
Designing and Implementing an Azure AI Solution
This course will prepare students to create Azure AI solutions. Specifically, this course will cover how to build a customer support chatbot using artificial intelligence from the Microsoft Azure platform, including language comprehension and pre-built AI functionality in the Azure Cognitive Services.
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Week 20-23
Capstone Project: Autonomous Cars
As part of this capstone project, students will design and train an artificial intelligence model to estimate the speed of a car based on dash cam footage and detect and recognize traffic signs. Students will apply course concepts and use a pretrain network to achieve project goals.