AI and Machine Learning Training

Our Artificial Intelligence and Machine Learning (AI and ML) training courses will teach your team how to combine deep learning, ML, and data science practices to build AI solutions for unique business challenges. Our AI courses include topics on Python, TensorFlow & Keras, Generative AI, Spark, AWS, and more. We can customize any AI course to meet your team's experience levels and goals.

Leverage the Power of AI to Streamline Processes and Make Predictions

Machine learning (ML) is a subset of Artificial Intelligence (AI) that allows computers to learn from data without any programming intervention. ML algorithms use data to identify patterns and learn from them, making it possible to automate tasks and predict outcomes.

Web Age Solution’s live, instructor-led AI and ML training courses are taught by data science experts who are also seasoned trainers. All courses incorporate real-world techniques and hands-on practice to build AI applications that can be tailored for your group.

For role specific AI/ML upskilling journeys see our programs for :

Data Scientists, ML Engineers, Software Engineers

Data Engineers, DevOps/Architects, Analysts, Managers

AI Training

Our Artificial Intelligence (AI) training courses teach your team how to combine deep learning, Machine Learning (ML), and AI practices to build AI solutions for unique business challenges. Our AI courses include topics on Ethical AI, AI Security, Generative AI, AI Engineering, Large Language Models (LLMs), and more.

We can customize any AI course to meet your team's experience levels and goals.

Our Top Courses
Machine Learning Training

Harness the power of AI and Machine Learning (ML) to transform your business. Web Age's Machine Learning courses teach attendees how ML algorithms, trained on data, can automate tasks, predict outcomes, and generate valuable insights. Master Python, Neural Networks (NN), Natural Language Processing (NLP), and more to efficiently build and deploy secure ML models. Web Age's customizable ML training programs give your team the skills to thrive in AI and ML.

Our Top Courses
Prompt Engineering Training

Unlock your creative potential using Generative AI with Web Age's Prompt Engineering courses. Attendees master the art of crafting and refining prompts in AI models, like OpenAI's GPT, to elicit custom responses. Our courses teach students to use Generative AI to generate text, code, images, and more. Learn from industry experts, master advanced prompting techniques, and explore diverse use cases across industries. 

Our Top Courses
Prompt Engineering for Developers: Mastering the Art of Conversational AI
Delivery: On-Site or Instructor-led Virtual

This Prompt Engineering course teaches software developers how to design and develop effective conversational AI applications using sound prompt engineering techniques. Participants learn how to create targeted custom prompts, resulting in more accurate and engaging conversational experiences. This AI course also teaches attendees techniques for designing, refining, and testing prompts.

Prompt Engineering: Techniques and Best Practices
Course ID: WA3307
Delivery: On-Site or Instructor-led Virtual

This Generative AI Prompt Engineering course teaches students how to design and refine prompts for natural language processing (NLP) models. Students learn to select the right inputs, questions, and context to ensure the model generates accurate and relevant outputs. This course also focuses on prompt engineering for generative NLP models such as GPT (Generative Pre-trained Transformer).

ChatGPT Basics
Course ID: WA3403
Delivery: On-Site or Instructor-led Virtual

This ChatGPT training course will teach you the fundamentals of prompt engineering for large language models (LLMs). Attendees learn how to craft effective prompts to guide LLMs in generating the desired output.  Students also learn about different prompting techniques, including zero-shot prompting, few-shot prompting, chain-of-thought prompting, and retrieval-augmented generation.

Nvidia Training
NVIDIA is the chip maker that became an AI superpower. With its invention of the GPU in 1999, NVIDIA sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI, and is fueling industrial digitalization across markets. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

Our Top Courses
Data Parallelism: How to Train Deep Learning Models on Multiple GPUs
Course ID: NV-DP-GPU
Delivery: On-Site or Instructor-led Virtual

Modern deep learning challenges leverage increasingly larger datasets and more complex models. As a result, significant computational power is required to train models effectively and efficiently. Learning to distribute data across multiple GPUs during deep learning model training makes possible an incredible wealth of new applications utilizing deep learning. Additionally, the effective use of systems with multiple GPUs reduces training time, allowing for faster application development and much faster iteration cycles. Teams who are able to perform training using multiple GPUs will have an edge, building models trained on more data in shorter periods of time and with greater engineer productivity.

Fundamentals of Accelerated Computing with CUDA Python
Delivery: On-Site or Instructor-led Virtual

This workshop teaches you the fundamental tools and techniques for running GPU-accelerated Python applications using CUDA® GPUs and the Numba compiler. You’ll work though dozens of hands-on coding exercises and, at the end of the training, implement a new workflow to accelerate a fully functional linear algebra program originally designed for CPUs, observing impressive performance gains. After the workshop ends, you’ll have additional resources to help you create new GPU-accelerated applications on your own.
Fundamentals of Accelerated Computing with CUDA C/C++
Delivery: On-Site or Instructor-led Virtual

This workshop teaches the fundamental tools and techniques for accelerating C/C++ applications to run on massively parallel GPUs with CUDA®. You’ll learn how to write code, configure code parallelization with CUDA, optimize memory migration between the CPU and GPU accelerator, and implement the workflow that you’ve learned on a new task—accelerating a fully functional, but CPU-only, particle simulator for observable massive performance gains. At the end of the workshop, you’ll have access to additional resources to create new GPU-accelerated applications on your own.
Other AI and Machine Learning Training
Applied Linear Algebra, Calculus, and Statistics for AI, ML, and Data Science
Course ID: WA3418
Delivery: On-Site or Instructor-led Virtual

Understanding the core concepts of artificial intelligence, machine learning, or data science is impossible without knowing the fundamentals of linear algebra, calculus, statistics, and probability. This training course teaches the essentials in the respective fields of knowledge to prepare the learners to start or advance their careers in AI, machine learning, or data science.

Spark and Machine Learning at Scale
Course ID: WA3290
Delivery: On-Site or Instructor-led Virtual

This Spark and Machine Learning training teaches participants how to build, deploy, and maintain powerful data-driven solutions using Spark and its associated technologies. The course begins with an introduction to Spark, its architecture, and how it fits into the Hadoop and Cloud-based ecosystems. Participants learn to set up Spark environments using DataBricks Cloud, AWS EMR clusters, and SageMaker Studio. In addition, students learn about Spark's core functionalities, including RDDs, DataFrames, transformations, and actions.

Building Applications with Large Language Models
Delivery: On-Site or Instructor-led Virtual

In this Large Language Models (LLMs) course, participants learn how to build practical, innovative, and impactful applications using LMMs like ChatGPT. The course covers model selection, API integration, and prompt engineering. Participants also explore techniques for optimizing AI-generated content to ensure content safety and address biases in AI-driven applications.

Frequently Asked AI Questions
What is Artificial Intelligence?

The replication of human intellectual processes by machines, particularly computer systems, is known as artificial intelligence. Expert systems, natural language processing, speech recognition, and machine vision are examples of AI applications.

Why do we need artificial intelligence?

Today, the amount of data that is generated, by both humans and machines, far outpaces humans’ ability to absorb, interpret, and make complex decisions based on that data. Artificial intelligence forms the basis for all computer learning and is the future of all complex decision making.

There are many useful applications of AI that have changed our lives such as Google Maps, self-driving cars, automated marketing, e-commerce recommendation systems, automated fraud detection, and many more.

What is Machine Learning and how does it differ from Artificial Intelligence?

Artificial Intelligence is the broader concept of endowing machines with intelligence, whether it is emotional intelligence, social intelligence, logical intelligence, planning, creativity, etc.

Machine Learning is a subfield of AI, it can be seen as a way to implement decision-making in AI and getting computers to learn.

Can I take AI Training online?

Yes! Our AI training is available as “onsite live training” or “online live training”. Onsite live AI training can be carried out locally on customer premises or in Web Age corporate training centers. Our live online AI training is carried out by way of an interactive, remote desktop.

We can customize any AI course to meet your team’s experience levels and goals.

What are the pros of AI?

Since the hype generated for Artificial Intelligence in the modern era is massive, it has a lot of pros.

Apart from the many job opportunities created by AI, it also has other pros, such as the completion of looping or repetitive tasks that humans need to perform without the disadvantage of a human-prone error.

AI has the ability to perform faster computations compared to human speed on a wide range of problems with precise results. There are also many real-life applications to make our daily lives simpler. The pros of Artificial Intelligence are limitless.