Machine learning skills are among the most sought-after in the technology industry today. Algorithms built on machine learning power the majority of trading activity on Wall Street, drive the recommendation engines at companies like Amazon, Spotify, and Netflix, and increasingly shape decisions 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 a wide range of 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.
