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Virtual: Machine Learning Corporate Training
Apply machine learning algorithms to solve real-world business problems from data cleaning to model evaluation. This practical group course teaches you the techniques behind recommendation systems and trading algorithms used by major tech companies.
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| Location |
Zoom Conference Platform detailsZoom is recommended. For Microsoft Teams, Google Meet or WebEx, provide the meeting link to CourseHorse in advance of the event.
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| Pricing |
$1,800 for up to 20 people
We're happy to discuss your training needs free of charge. Reach out for a free consultation and let us know which skill your team is interested in, your preferred custom training options, and the approximate number of participants you’ll have so we can create a package for you. Send us an email or give us a call today! |
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| Duration |
Up to 7 hours For a shortened session, please request desired length in special requests at checkout.
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| Group Size |
Up to 20 people Group size can be changed after booking if needed.
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| Materials | None required | |||||||||||||||
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General Notes
Supported Platforms for Virtual Events: Zoom is our recommended platform, but we can accommodate Google Meets, Microsoft Teams, and WebEx if you provide the meeting link to CourseHorse in advance of the event. PoliciesPrice Match GuaranteeIf you find a similar event with a competitor at a lower price, we’ll gladly match it. This applies to events of comparable description and duration. Simply provide the details when booking, or within 72 hours of your booking, and we’ll ensure you get the best value. Contact an event concierge to get started. Rescheduling & Cancellation PolicyReschedule or cancel your event by emailing us at [email protected].
Rescheduled events must occur within 1 year of the original event. |
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Description
Explore machine learning applications in trading, recommendation engines such as Amazon, Spotify and Netflix, and decision-making across healthcare, finance and consumer technology.
This course begins with linear and logistic regression, two of the most reliable and widely used approaches to supervised learning. From there, you will explore algorithms with different theoretical foundations, including k-nearest neighbors, decision trees, and random forests. Along the way, key statistical concepts such as bias, variance, and overfitting are introduced and explained clearly. You will also learn how to evaluate model accuracy and how to make informed decisions when selecting features and algorithms.
The focus throughout is on practical, applicable skills for solving real problems with machine learning. The mathematical foundations of each algorithm are explained visually rather than through formal mathematics, making the concepts accessible while remaining rigorous. Students are expected to be comfortable writing Python programs and working with NumPy and Pandas before enrolling.
Prerequisite:
Comfort with Python and its data science libraries, specifically NumPy and Pandas, is required. Students who have not previously worked in Python should complete our Python for Data Science Bootcamp before enrolling in this course.
Topics Covered at a Glance:
- Cleaning and balancing datasets using the Pandas library
- Applying machine learning algorithms, including logistic regression and random forest, using scikit-learn
- Selecting effective features to use as algorithm inputs
- Correctly splitting data into training, test, and cross-validation sets
- Core theoretical concepts: overfitting, variance, and bias
- Evaluating and measuring the performance of your machine learning models
Flexible Training Solutions for Your Team
Group Vouchers and Scheduled Classes
Group vouchers are available so employees can attend sessions at their convenience, with options on weekdays, weeknights, and weekends. Courses run live online and in person at our Midtown Manhattan offices. Larger voucher packages include a custom registration tracking portal.
With various courses on the calendar, employees can choose sessions that match their current proficiency, schedule, and preferred format.
Practical Skills from Working Industry Professionals
Participants leave training ready to apply their skills right away, with all course files to keep for future reference.
Our hands-on curriculum is designed around real data science and machine learning challenges. Training is available on-site at your office, at our Midtown Manhattan location, or through live virtual instruction, and can be fully customized to your organization's needs.