Course NameLength
3D Computer Vision Engineering Workshop2 days
Advanced Topics in Deep Learning and Neural Networks2 days
AI in Engineering and Systems Engineering Bootcamp2 days
AI-Driven Contract Pre-Award, Award and Post-Award Management Workshop2 days
AI-Driven Cost and Price Analysis2 days
AI-Driven Critical Thinking for Problem Solving Workshop2 days
AI-Driven Performance-Based Service Acquisition2 days
AI-Driven Systems Engineering Decision Making2 days
AI/ML and Intelligent Automation for DoD2 days
AI/ML Training for Managers1 day
AR/VR/MR for Managers1 day
Artificial Intelligence (AI) Ethics Seminar2 days
Artificial Intelligence / Machine Learning System Safety Workshop2 days
Artificial Intelligence Training Bootcamp | AI Training3 days
Artificial Intelligence | Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD)3 days
Biohacking and Human Performance Optimization Workshop2 days
Breakthrough Ai-Driven Problem Solving Workshop2 days
Data Analysis and Modeling Capstone2 days
Fundamentals of Deep Learning2 days
Introduction to Artificial Intelligence and Machine Learning2 days
Machine Learning and Computer Vision Engineering Training Workshop2 days
Machine Learning for Control Training3 days
Machine Learning Training Bootcamp3 days
Overview Of Quantum Computers2 days
Overview of Quantum Internet2 days
Overview Of Quantum Sensors2 days
Overview of Quantum Technologies for Leadership2 days
Predictive Analytics and Machine Learning Models2 days
Quantum and Artificial Intelligence Technologies for Next Generation Armament Systems2 days
Quantum Technology for Non-Engineers2 days
Systems Engineering and Project Management with AI2 days
Ultra-Secure Communications with Quantum Technologies2 days
Virtual Reality (VR) Training Boot Camp2 days

Artificial Intelligence (AI) and Machine Learning (ML)


Machine learning (ML) and artificial intelligence (AI) are yet more technological advances that organizations need to implement in order to stay competitive in their industry.

Machine learning extracts meaningful insights from raw data to quickly solve complex, data-rich business problems.

The keys here are machine learning algorithms. ML algorithms learn from the data iteratively and allow computers to find different types of hidden insights without being explicitly programmed to do so.

Who Should Attend:
Professionals seeking to enhance their AI and Machine Learning expertise, including data scientists, engineers, analysts, and IT professionals. Ideal for organizations looking to upskill their teams and harness AI’s potential for innovation.

Machine learning in business helps in enhancing business scalability and improving business operations for companies across the globe. Artificial intelligence tools and numerous ML algorithms have gained tremendous popularity in the business analytics community.

Factors such as growing volumes, easy availability of data, cheaper and faster computational processing, and affordable data storage have led to a massive machine learning boom.

If done correctly, machine learning can serve as a solution to a variety of business complexities problems, and predict complex customer behaviors. Major technology giants figured this out some time ago.

Google, Amazon, Microsoft, etc., have in fact come up with their own Cloud Machine Learning platforms.

In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.

Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress toward human-level AI.

Machine learning is an important component of the growing field of data science. Through the use of statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects.

These insights subsequently drive decision making within applications and businesses, ideally impacting key growth metrics. As big data continues to expand and grow, the market demand for data scientists will increase, requiring them to assist in the identification of the most relevant business questions and subsequently the data to answer them.

“Deep” machine learning can leverage labeled datasets, also known as supervised learning, to inform its algorithm, but it doesn’t necessarily require a labeled dataset.

It can ingest unstructured data in its raw form (e.g., text, images), and it can automatically determine the set of features which distinguish different categories of data from one another.

Unlike machine learning, it doesn’t require human intervention to process data, allowing us to scale machine learning in more interesting ways.

AI and Machine Learning Training Courses by Tonex

Our Machine Learning Training Courses covers a wide array of topics including:

  • The Basics of Machine Learning
  • Popular Machine Learning Methods
  • Terminology and Principles
  • Machine Learning Tools and Algorithms
  • Applied Artificial Intelligence and Machine Learning
  • Principles of Neural Networks
  • Introduction to Deep Learning

Our Machine Learning Training Bootcamp is especially beneficial for busy professionals who want to stay current in their fields but have limited time to be away from the office.

Attendees learn, comprehend and master ideas on machine learning concepts, key principles, techniques including: supervised and unsupervised learning, mathematical and heuristic aspects, modeling to develop algorithms, prediction, linear regression, clustering, classification, and prediction.

Our Machine Learning for Control Training is a unique course that explores the fundamentals of control theory, an area of engineering related to control of continuously operating dynamical systems in engineered processes and machines.

Remember, Tonex courses can be tailored to your needs.

Contact us for more information, questions, comments.

AI and Machine Learning