Course NameLength
3D Computer Vision Engineering Workshop2 days
Advanced AI and Machine Learning for Security Operations2 days
Advanced AI Security: Understanding and Mitigating Risks in LLM and GenAI2 days
Advanced Topics in Deep Learning and Neural Networks2 days
AI and Education: Teaching and Learning with Intelligent Systems2 days
AI and Human Interaction Design2 days
AI Ethical Frameworks Workshop2 days
AI for Managers2 days
AI for Non-Engineers2 days
AI in Creative Industries: A New Collaborative Frontier2 days
AI in Engineering and Systems Engineering Bootcamp2 days
AI in the Workplace: Skills for the Future2 days
AI Leadership Workshop2 days
AI Manifesto Workshop2 days
AI Systems Engineering and Cybersecurity: Design, Threat Modeling, and Defense2 days
AI-based OSINT (Open Source Intelligence): Social Media Monitoring, Collections, Investigations/Reporting, Analytics2 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
Applied Data Science and AI/Machine Learning for Cybersecurity2 days
AR/VR/MR for Managers1 day
Artificial Intelligence (AI) Certificate2 days
Artificial Intelligence (AI) Ethics Seminar2 days
Artificial Intelligence / Machine Learning System Safety Workshop2 days
Artificial Intelligence Ethics and Trust2 days
Artificial Intelligence for Non-Engineers1 day
Artificial Intelligence Problem Solving Workshop2 days
Artificial Intelligence Training Bootcamp | AI Training3 days
Artificial Intelligence | Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD)3 days
Artificial Intelligence: Business Strategies and Decisions2 days
Biohacking and Human Performance Optimization Workshop2 days
Breakthrough Ai-Driven Problem Solving Workshop2 days
Building and Delivering Machine Learning Models for Operational Management2 days
Cognitive Engineering for AI Systems Training2 days
Data Analysis and Modeling Capstone2 days
Developing AI Solutions with Human-Centric Design2 days
Engineering of AI and Machine Learning Systems Training2 days
Ensuring Safe, Secure, and Trustworthy Development and Use of AI, LLM and GenAI2 days
Essentials of Digital Technology Training2 days
Ethical AI: Principles and Practices2 days
Financial Engineering with AI Technologies2 days
Fundamentals of Deep Learning2 days
Fundamentals of Trustworthy AI2 days
Generative AI Security: Principles and Practices2 days
Healthcare AI Systems Engineering Training2 days
Human-AI Collaboration in Healthcare2 days
Introduction to AI Regulatory Frameworks2 days
Introduction to AI Safety, Security and Quality2 days
Introduction to Artificial Intelligence and Machine Learning2 days
Introduction to Human-AI Collaboration2 days
Introduction to Systems Thinking for Leadership2 days
Introduction To Trusted Autonomy And Artificial Intelligence2 days
IoT Systems Engineering with AI Applications Training2 days
Machine Learning and AI for Non-Engineers2 days
Machine Learning and Computer Vision Engineering Training Workshop2 days
Machine Learning for Control Training3 days
Machine Learning for Cybersecurity Engineers2 days
Machine Learning for Reliability Engineers2 days
Machine Learning for Safety Engineers2 days
Machine Learning Training Bootcamp3 days
Machine Learning, and Artificial Intelligence Using Python Workshop2 days
Overview of AI Manifesto2 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
Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence2 days
Securing Artificial Intelligence (AI)2 days
Strategic Decision-Making with AI2 days
Systems Engineering and Project Management with AI2 days
The Pillars Of AI and Machine Learning2 days
Ultra-Secure Communications with Quantum Technologies2 days
Virtual Reality (VR) Training Boot Camp2 days
Zero Trust AI Infrastructure Training2 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.

Many companies are already using forms of AI or machine learning (ML) for everything from automation of manual processes to predicting and fulfilling customer demand.

Most companies no longer resist the use of AI/ML. But many organizations are still befuddled on the best way to utilize these technologies.

Experts believe the first step is for companies to identify and clarify the most profitable use cases in order to determine their future AI investment and development needs.

For example, take the financial sector. One widespread use of AI and ML is in fraud detection. Visa, Mastercard and PayPal (all US) are using machine-learning algorithms to analyze data on customer behavior captured over several decades.

Such analysis can detect oddities in account activities and identify fraudulent activity in mere milliseconds at any point in the transaction cycle. According to recent reports, AI and ML have been very successful in reducing fraud.

Another prominent use of AI is in the healthcare industry. AI is being used in healthcare facilities and pharmaceutical industries. Allocation of resources and drug discovery are two of the many ways AI is being used.

Diagnostics is another area with potential, with AI used to check patients’ symptoms against possible causes or to analyze scans. Early adopters include Chinese health apps such as Ping An’s Good Doctor and Chinese hospitals, particularly in Shanghai, which allegedly wants to become a base for healthcare AI.

Electric grids are also investing in AI.

In the US, the Department of Energy has put AI at the center of its smart grid strategy, while in the UK the National Grid has teamed up with IBM to develop cloud-based analytics. These initiatives allow for real-time monitoring of power grids and the ability to forecast and respond to surges in output or demand.

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.

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.

Remember, Tonex courses can be tailored to your needs.

Contact us for more information, questions, comments.

AI and Machine Learning