Analytics for the Practicing Professional

About the series

You are a subject matter expert in your field. To help you multiply your effectiveness, we will teach you to quickly understand and deploy basic and advanced anaytics techniques including articificial intelligence and natural language processing.We beliveve analytics is best done by the subject matter expert.

Classes are taught using real life industrial and other data sets. They can be taught on site, or live via Zoom. During class, students learn the techniques by working under supervision on a separate but real life data set. At the end of each course, you will be able to apply specific techniques to your own data set.

Each course is 8 hours long, hands-on, and can be delivered live via Zoom (or at your site). Students write code under supervision during class time. The series starts by transitioning the practicing professional to Python to help them access powerful public domain artificial intelligence and other analytics tools. In the second course of the series, Exploratory Data Analysis (EDA), you are taught to handle various data related issues such as importing/exporting, error handling, and then to gain a basic understanding of the data using various EDA techniques. In the next course, Foundational Analytics (FA), you learn the essential analytics techniques such as filtering, data aggregation, linear and non-linear correlation, auto-correlation and cross correlation and hypothesis testing. In the course Artificial Intelligence (AI), you learn to apply neural networks and random forests, while also gaining an understanding of concepts such as generalization. In the Natural Language Processing (NLP), course you learn about the core concepts such as normalization of text, word frequencies, semantics concepts and tools such as lemmatization, parts of speech and dependencies, and classification of text using random forests.

The courses are taught by analytics experts of the ai.sys research group at the University of Utah.

Transition to Python

Python is a major platform for big data analytics. Therefore, this hands-oncourse helps the practicing professional transfer their programming skills to Python. It is first in the series of courses designed to develop big data analytics skills in the professional. It introduces basic Python programming (conditional statements, iterations, arrays and functions), and builds Python skills that will eventually be used to retrieve, manipulate, and manage large sets of data that engineers encounter in industrial settings. Students will get hands on programming experience through in-class coding exercises.

Pre-requisites: Prior programming experience. Rusty skills are ok.

Dates and Duration: 8 hours total. Contact for date.

Cost: $800 (for live Zoom). Inquire about group discounts for organizations.

For syllabus or questions, contact rajive.ganguli@utah.edu

Exploratory Data Analysis

Course Description: This hands-on course is second in the analytics series of courses. The goal of this Python based course is to impart tools that help one to develop a basic understanding of data. It teaches students how to read and write data sets, address data conversion issues and plot. It covers data selection, characterization using QQ plots and box plots, basic statistics and hypothesis testing. Students will work with real life data sets and learn to make sense of it. Student will be introduced to the Python packages numpy, scipy and matplotlib and pandas. Students will work with a real life data set in class to apply the techniques in a guided manner.

Pre-requisites: Transition to Python

Dates and Duration: 8 hours total. Contact for date.

Cost: $800 (for live Zoom). Inquire about group discounts for organizations.

For syllabus or questions, contact rajive.ganguli@utah.edu

Foundational Analytics

This hands on course covers topics that help one to gain an intuitive sense of the relationships that exist in the data. This Python based course starts with filtering of data (including for time series data) and various forms of aggregation (disjointed and moving windows). It introduces and demonstrates linear and non-linear correlation. The concept of lag, and auto-correlation are covered next. This is followed by multivariate regression, and understanding the process of how to determine the importance of various inputs. Students will work with a real life data set in class to apply the techniques in a guided manner.

Pre-requisites: Exploratory Data Analysis

Dates and Duration: 8 hours total. Contact for date.

Cost: $800 (for live Zoom). Inquire about group discounts for organizations.

For syllabus or questions, contact rajive.ganguli@utah.edu

Artificial Intelligence

This hands on course introduces neural networks and random forests. The content of this Python based course includes short lectures to introduces both topics, and the concepts that apply to both topics such as generalization and value of ensemble models. This is followed by hands on exercises, including exercises to determine the importance of different inputs.

Pre-requisites: Exploratory Data Analysis, Foundational Analytics (preferred)

Dates and Duration: 8 hours total. Contact for date.

Cost: $800 (for live Zoom). Inquire about group discounts for organizations.

For syllabus or questions, contact rajive.ganguli@utah.edu

Natural Language Processing

This hands-on Python based course on natural language processing (NLP) helps the student get started on applying NLP. It introduces concepts for pre-processing of text including tokenization, basic editing (changing case, removal of certain characters etc), complications with dates, and removal of stopwords. The courses then progress to the first steps on NLP including word frequencies, word clouds and linguistic features, such as lemmatization and parts of speech. The powerful machine learning technique random forests are introduced for classification of text. The introduced tools are used to analyze safety reports from the Mine Safety and Health Administration (MSHA).

Pre-requisites: Exploratory Data Analysis

Dates and Duration: 8 hours total. Contact for date.

Cost: $800 (for live Zoom). Inquire about group discounts for organizations.

For syllabus or questions, contact rajive.ganguli@utah.edu

The courses are taught by Dr. Rajive Ganguli and/or Dr. Rambabu Pothina

Please visit the ai.sys group page to learn more about their research.

Registration Information

Please click here to register.

Policies

• You must have access to a modern computer and stable high speed internet to take the courses.
• You may withdraw with a full refund up to 4 weeks before start of class. After that period, no refunds are made. However, if you do withdraw before the first day of class, as a courtesy, you will be enrolled in a future class.

Special Offerings

Courses can be offered on site and/or on dates suitable for your organization.

Group Discounts

A 10% discount is available for groups of 10 or more. A 20% discount is available for groups larger than 25.

Inquiries

To inquire about special offerings, group discounts etc. contact rajive.ganguli@utah.edu