Applied Machine Learning

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The best way to master Machine Learning is to understand the core concepts, be capable of explaining them with simple everyday examples, and be able to apply those to solving business problems. This course focuses on building up your theoretical and practical knowledge so that you can understand how to identify ML problems, choose the right algorithms for solving the problem at hand, build robust models in Python, and explain your models and communicate their results in common business language for colleagues, clients, and executives. You’ll learn from real world examples and apply your learnings to a variety of business problems.

Learn from a world-class industry expert

Dr. Kirk Borne is the Chief Science Officer at AI startup DataPrime and the founder of Data Leadership Group LLC. He is a career data professional, data science leader, and research astrophysicist. From 2015 to 2021, he was Principal Data Scientist, Data Science Fellow, and Executive Advisor at Booz Allen Hamilton.

Previously, Kirk was professor of Astrophysics and Computational Science at George Mason University. Before that, he spent 20 years supporting data systems activities for NASA space science missions, including the Hubble Space Telescope.

He has been named by many media outlets as a top worldwide influencer on social media, promoting big data analytics, data science, machine learning, AI, data & AI strategy, and data literacy for all.

He has spoken at hundreds of events worldwide, for which he has been the conference keynote speaker at dozens of those, including TEDx, Global AI Summit (online), Marketing Analytics & Data Science (San Francisco), Big Data London, and more.

700  1,000  
Level - Learnify X Webflow Template
Level : 
Intermediate
Duration - Learnify X Webflow Template
Date : 
10 AM EST; Mar 27, Mar 30, Apr 3 and Apr 6
Lessons - Learnify X Webflow Template
Live Sessions : 
4 live courses (2 hours each) with weekly office hours and recordings
Lifetime access
Lifetime Access
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Course teacher
Dr. Kirk Borne

Prerequisites:

Understanding of the different types of machine learning algorithms (unsupervised: clustering; and supervised: classification).

This course is for:

Intermediate learners of machine learning and data analytics.

What you will be able to do after this course:

Participants will be able to demonstrate expertise in deploying both common and uncommon applications of ML concepts, techniques, and algorithms to a variety of business problems

What is unique about this course?

Testimonials

Recommended by experts

Tulga picture
Tulga
Principal Global Analytics Solution Architect at Johnson & Johnson

Dr. Kirk Borne course was greatand the choice of the instructor was spot on. I have been following Dr.Kirk Borne for a long time and he is a legend, with a great personality.

Connor picture
Connor
Data Operations Analyst at FINRA

During the Applied Machine Learning course, our instructor brought up a money laundering use case which is very useful since it's a critical part of my daily work. I also enjoyed joining the office hours to get feedback on the different assigments I had to work on.

Ilham picture
Ilham
Senior Data Engineer at Spotify

Good to have a TA and not just the instructor. Loved the examples of how to apply Machine Learning in real life

Trusted by learners from top companies

Additional information about the course

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Session 1: Meet your instructor Kirk

Lessons
Date
Mon Mar 20th, 2023 - 03:00PM

We're excited to kick-off this cohort of the Applied Machine Learning Course with Dr. Kirk Borne.

This is an introductory session where you will get a chance to meet your instructor Dr. Kirk Borne, connect with other course participants from different companies, get important information about the cohort and ask questions.

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Session 2: Modeling and Machine Learning Concepts

Lessons
Date
Mon Mar 27th, 2023 - 03:00PM

Focus on the basics, foundations, and concepts that are essential for progressing on the journey of expanding one’s expertise in ML techniques, algorithms, and applications, including supervised vs. unsupervised learning, feedback and optimization loops, accuracy vs. precision, benefits of high-variety data, bias and ethical modeling, types of analytics outcomes, and examples of successes and failures in the field.

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Session 3: Common Business Applications of ML Algorithms

Lessons
Date
Thu Mar 30th, 2023 - 03:00PM

Focus on specific applications of ML algorithms to common business problems, including customer segmentation (personalization and recommender engines), outlier detection (anomaly, fraud, and surprise discovery), predictive analytics (forecasting, predictive maintenance), and association analysis (link discovery, knowledge graphs, marketing attribution).

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Session 4: Uncommon (Atypical) Applications of Typical ML Algorithms

Lessons
Date
Mon Apr 3rd, 2023 - 03:00PM

Focus on solving a business problem in an unexpected way with an ML algorithm or technique that is more commonly used for a very different problem or in a very different application domain. A common thread throughout this module is Forecasting 2.0 - going beyond traditional forecasting modeling techniques, into the realm of early warning detection within your business applications through precursor analytics.

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Session 5: Analytics Mastery in Business and Beyond

Lessons
Date
Thu Apr 6th, 2023 - 03:00PM

Focus on the steps to analytics mastery, including matching the right algorithm and technique to the right business problem, data storytelling, decision science, the internet of things (IoT, which will produce massive quantities of real-time streaming data in the coming decade, generating a multi-trillion dollar market, requiring a data-literate analytics-equipped IoT-savvy workforce), and the soft skills that must accompany the hard skills for long-term career success and advancement.

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Session 6: Meet your Teaching Assistant Raphael Taiwo Alabi, PhD (Lead Machine Engineer at DocuSign)

Lessons
Date
Sat Mar 25th, 2023 - 05:00PM

Come meet Raphael (Lead Machine Engineer at DocuSign) to ask him any questions related to the course.

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Session 7: ML Use Case Presentation from DocuSign

Lessons
Date
Wed Apr 5th, 2023 - 05:00PM

Raphael will walk you through a ML Use Case Presentation from DocuSign.

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Session 8: Meet your Teaching Assistant Raphael Taiwo Alabi, PhD (Lead Machine Engineer at DocuSign)

Lessons
Date
Wed Apr 12th, 2023 - 05:00PM

Come meet Raphael (Lead Machine Engineer at DocuSign) to ask him any questions related to the course.

Frequently asked questions