Enterprise AI and Data Science Training Courses

Learn the foundations of AI and Data Science, and master the skills necessary to build state-of-the-art solutions, and technical strategy to transform your enterprise.

 

Purpose

There is currently a shortage of properly trained AI talent, and unfortunately, many companies find it difficult to hire good AI practitioners.

 

Our goal in these courses is to provide you with the fundamental techniques that you can use to integrate state-of-the-art AI capabilities into your enterprise and applications.

 

After completing these courses, you will have a deep understanding of how to set the technical direction for your AI project.

 

You will also develop in-house AI capabilities and talent to strategically execute on projects that deliver real value to your enterprise.

 

Follow our proven training track to provide broad AI knowledge to executives, business leaders, technical teams and product owners, or we can develop a customized curriculum for your team.

 
 
 
 
 
 

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AI Training Courses

Course Details

Intro to Modern Data Analysis for Data Science

Course overview:

 

  • This course will help prepare you for your path towards data science and AI by teaching you how to analyze data of all types using open source programming languages.

  • You can expect to learn several critical data science skills such as the Unix command line, fundamentals of open source programming, data structures, data analysis packages, interactive visualization, computational statistics, regular expressions, object-oriented programming, Git, and GitHub.

  • Hands-on coding, pair programming, open-source tools and frameworks

 

This Intro to Modern Data Analysis for Data Science course will consist of the following major tasks:

 

  • Command line

  • Data structures and data types

  • Data analysis packages

  • Plotting packages

  • Computational Statistics

  • Regular expressions

  • Interactive visualization

  • Modules and classes

  • Git and GitHub

 

Prerequisites: Recommend some knowledge of either SQL, Excel, SAS, or basic programming experience necessary.

Training options: We can teach this course at your organization, remotely, or at our office location.

Class size: Up to 20 participants per session

Length: 3 Days

Intro to Exploratory Data Analysis (EDA) & Insight Discovery

Course overview:

 

  • This course will help you improve your ability to do the science and research part of Data Science through the latest techniques and methods using a dynamic, iterative problem-solving process.

  • You can expect to learn several critical data science skills such as the research process, question development, data acquisition, cleansing data, analysis, experimentation, insight discovery, visualization, and telling stories with data.

  • Hands-on coding, pair programming, open-source tools and frameworks

 

This Exploratory data analysis (EDA) course will consist of the following major tasks:

 

  • Frame hypotheses and develop investigation themes to explore

  • Collect and Wrangle data

  • Assess the quality of data

  • Profile data

  • Explore each individual variable in the dataset

  • Assess the relationship between each variable and the target

  • Assess interactions between variables

  • Explore data across many dimensions

  • Identify metrics that are manageable and predictable

 

Prerequisites: Recommend some knowledge of either SQL, Excel, SAS, or basic programming experience necessary.

Training options: We can teach this course at your organization, remotely, or at our office location.

Class size: Up to 20 participants per session

Length: 3 Days

Applied Machine Learning & Deep Learning

Course overview:

 

  • This course will help you learn the common tasks in a machine learning project and how to complete important subtasks in an ML workflow.

  • You can expect to learn critical ML skills such as how to define your ML problem, exploratory data analysis, data preparation, model evaluation, model tuning, deployment.

  • Hands-on coding, pair programming, open-source tools and frameworks

 

This Machine Learning & Deep Learning course will consist of the following major tasks:

 

  • Intro Machine Learning.

  • Open Source Frameworks

  • Data Acquisition

  • Data analysis using EDA

  • Interactive Data Visualization

  • Data Preprocessing

  • Types of ML & DL Algorithms

  • Supervised, Unsupervised, Graph Networks, Transfer, Reinforcement, Multi-task, Generative, End-to-end etc

  • Feature Extraction and Selection

  • Evaluation Methods, Metrics, Parameter Tuning

  • Model Selection, Ethics, Bias

  • Pipelines, Serialization, Reproducibility

  • Deployment, Container, Orchestration, Apps

 

Prerequisites: Linear algebra, Data structures, Computational Statistics, and basic programming experience necessary.

Training options: We can teach this course at your organization, remotely, or at our office location.

Class size: Up to 20 participants per session.

Length: 3 Days.

 

Applied Data Science

Course overview:

 

  • This course will help you apply the specific subtasks in a data science project end-to-end to create value.

  • You can expect to apply important data science skills for building applications such as iterative prototyping, exploratory data analysis, interactive visualization, applied machine learning, and Web apps.

  • Hands-on coding, pair programming, open-source tools and frameworks

 

This Applied Data Science course will consist of the following major tasks:

 

  • Applied Machine Learning.

  • Open Source Frameworks

  • Data Acquisition

  • Exploratory Data Analysis

  • Interactive Data Visualization

  • Data Engineering

  • Classification, Regression, Clustering, Text, Network Analysis etc.

  • Deployment, Apps

  • Ethics and Bias

 

Prerequisites: Linear algebra, Data structures, Computational Statistics, General ML Knowledge, and Basic Programming experience necessary.

Training options: We can teach this course at your organization, remotely, or at our office location.

Class size: Up to 20 participants per session

Length: 3 Days

 

Applied AI for Intelligent Systems

Course overview:

 

  • This course will help you build key skills for an AI Project and produce a fully functioning Intelligent System that improves over time and achieves success.

  • You can expect to apply important AI skills for building applications such as iterative prototyping, exploratory data analysis, interactive visualization, applied deep learning, and Web apps.

  • How to orchestrate an Intelligent System over its life-cycle.

  • Hands-on coding, pair programming, open-source tools and frameworks.

 

This Applied AI course will consist of the following major tasks:

 

  • Applied Deep Learning.

  • Open Source Frameworks

  • Interactive Data Visualization

  • Classification, Regression, Clustering, Collaborative Filtering, Embeddings, NLP, Vision, Speech, Generative models etc.

  • Advanced Deployment, Apps, Data Pipelines

  • Ethics and Bias

 

Prerequisites: Linear algebra, Data structures, Computational Statistics, General ML/DL Knowledge, and Basic Programming experience necessary.

Training options: We can teach this course at your organization, remotely, or at our office location.

Class size: Up to 20 participants per session

Length: 3 Days

What to Expect

Upon completion, attendees will:

  • Build a working knowledge of applied AI and Data Science concepts and algorithms

  • Be able to develop AI models for vision, language, speech, and multimodal systems  

  • Have new skills to solve real-world problems with AI using a variety of data sources

  • Understand the typical roles and responsibilities of an AI Team

  • Transform your enterprise with AI and create a positive impact on the world

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Chicago, IL 60642

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