Machine Learning for Advanced Analytics

Success in business depends largely on making faster and more accurate decisions to solve complicated problems. That speed and accuracy can hinge upon the ability to apply analytics to plumb data for meaningful patterns and predict future trends. For large sets of data associated with customers, business processes, and market economics, machine learning is a cornerstone of analytics in almost all industries. 

In this hands-on, accelerated course, you will learn the underlying principles for a wide variety of machine learning methods and algorithms, as well as the procedures to assess their validity in different applications. You will apply machine learning languages R and Python to select, build and use predictive models.

The course also covers data visualization, enabling you to examine the trends and patterns in big data problems. In particular, you will gain expertise in the data visualization tools ggplot2 for R and Matplotlib and Seaborn for Python. Applications for the course content include business intelligence, data mining/warehousing, service delivery, product development, marketing, and process improvement.

If you complete this course and either the Deep Learning with TensorFlow course or the Natural Language Processing course, you are eligible to receive the Caltech CTME Data Analytics Certificate.

Benefits

Participants will learn how to:

• Build machine learning models using the most widely-used tools (R and Python)
• Assess and compare models developed by different algorithms
• Deploy machine learning models to solve practical business problems
• Recommend the best machine learning algorithms for detecting trends in large, noisy data sets
• Compare and contrast data mining and machine learning techniques based on their mathematical assumptions, scalability, limitations, and parameters

Who should attend

This program is for professionals seeking to optimize business performance in high-tech companies. Applications include business intelligence, data mining/warehousing, service delivery, product development, marketing, and process improvement.

Schedule

Classes are held in a Hybrid environment. This course now runs every Saturday from 8:00am to 12:00pm PT at the Caltech campus in Pasadena, CA. Since this class is now hybrid, participants also have the option of attending this class remotely via Zoom. There are 4 hours of instruction every Saturday for 6 Days, which makes a total of 24 instruction hours. During the week before each session you will receive emails containing location-specific instructions.

Fee: $2130 for the program. Payment is due (or credit card charged) on the Friday prior to first day of the course. You may pay the entire program fee of $2130 in one payment, or you may pay the program fee in 3 increments of $710.

Hours and Credits: Participants will earn 2.4 Continuing Education Units (CEUs).

Grading: These programs are based on a Pass/Fail grading system.

Instructor

Ash Pahwa, PhD