Everything You Need to Know: Top Artificial Intelligence and Machine Learning Courses

Taylor Karl
/ Categories: Resources, Training Trends
Everything You Need to Know: Top Artificial Intelligence and Machine Learning Courses 423 0

With the latest advances in artificial intelligence (AI) and machine learning (ML) technology, you've probably seen and heard the buzz around some of the latest groundbreaking algorithms. A virtual assistant known as ChatGPT relays information like a human would in conversation. With Lensa, users can create magic avatars with "face data" to become re-imagined as medieval kings or woodland princesses.

Are you prepared to integrate AI and machine learning into your organization to optimize your business results? What was once a futuristic concept is now a reality, with AI being used in various industries and applications. From self-driving cars and virtual assistants to medical diagnosis and financial trading, AI is making its presence felt in our daily lives. Here are some of the top Artificial Intelligence (AI) and Machine Learning (ML) courses you can use to help accomplish your business goals:

United Training Artificial Intelligence Courses

Microsoft Azure AI Fundamentals

Azure AI Fundamentals is best suited for students with both technical and non-technical backgrounds that have foundational knowledge of machine learning and artificial intelligence concepts and related Microsoft Azure services. This course will teach you how to use Azure services to create machine learning, computer vision, and natural language processing solutions through hands-on activities. Data science and software engineering experience is recommended but not required. Additionally, awareness of cloud basics and client-server applications would be beneficial.

Course Objectives:

  • Describe Artificial Intelligence workloads and considerations
  • Describe the fundamental principles of machine learning on Azure
  • Describe features of computer vision workloads on Azure
  • Describe characteristics of Natural Language Processing (NLP) workloads on Azure

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Designing and Implementing an Azure AI Solution

Designing and Implementing an Azure AI Solution is for software engineers that are familiar with Azure and the Azure portal, C# or Python programming, and familiarity with JSON and REST programming semantics. This course will teach you how to create AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure.

Course objectives:

  • Describe considerations for AI-enabled application development
  • Create, configure, deploy, and secure Azure Cognitive Services
  • Develop applications that analyze text
  • Develop speech-enabled applications

Cisco Introduction to Artificial Intelligence

Cisco Introduction to Artificial Intelligence (CIAI) v1.0 is for students who understand server design and architecture. This course will teach you about Big Data and Data Science concepts, Artificial Intelligence, Machine Learning, and Deep Learning essentials, and much more.

Course objectives:

  • List and describe the images, concepts, significant features, algorithms, and benefits of AI/ML/DL
  • Neural Networks
  • Natural Language Processing fundamentals, techniques, and deployment
  • Kubernetes
  • AI server requirements
  • Data Science and Infrastructure AI Tools and software

AI for Business Professionals

AI for Business Professionals (AIBIZ™) is designed for managers, business leaders, and other decision makers who are interested in understanding the disruptive impact AI will have on their organization’s business results. Additionally, those genuinely interested in AI and what its impact will be are also welcome.

Course objectives:

  • Describe AI fundamentals and approaches to Machine Learning (ML) and Deep Learning (DL)
  • Analyze how AI is implemented in data science, search engines, Natural Language Processing (NLP), computer vision, and robotics
  • Identify the benefits, challenges, and business use cases of AI

Certified Artificial Intelligence (AI) Practitioner

Certified Artificial Intelligence (AI) Practitioner is for students with several years of computing technology experience, including some aptitude in computer programming. This course shows how to apply various approaches and algorithms to solve business problems through artificial intelligence (AI) and machine learning (ML), how to follow methodical workflows to develop sound solutions, use open source, off-the-shelf tools to develop, test, and deploy those solutions. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course is designed for those who have several years of experience with computing technology, including some aptitude in computer programming.

Course objectives:

  • Specify a general approach to solve a given business problem that uses applied AI and ML
  • Collect and refine a dataset to prepare it for training and testing
  • Train, tune, and finalize a machine learning model and present results to the appropriate audience
  • Build linear regression, classification, and clustering models
  • Build decision trees and random forests, support-vector machines (SVMs) and artificial neural networks (ANNs)
  • Promote data privacy and ethical practices in AI and ML projects

United Training Machine Learning Courses

The Machine Learning Pipeline on AWS

The Machine Learning Pipeline on AWS course is designed for developers, solutions architects, data engineers, and anyone who wants to learn about the ML pipeline via Amazon SageMaker (even if you have little to no experience with ML). This course utilizes hands-on learning, so students get to choose a project to work on and then apply the skills and knowledge learned in each phase of the pipeline. The project options are fraud detection, recommendation engines, or flight delays.

Course objectives:

  • Select and justify the appropriate ML approach for a given business problem
  • Use the ML pipeline to solve a specific business problem
  • Train, evaluate, deploy, and tune an ML model in Amazon SageMaker
  • Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS

Google Cloud Fundamentals: Big Data and Machine Learning

Google Cloud Fundamentals: Big Data and Machine learning is designed for data scientists, data analysts, business analysts beginning to work with the Google Cloud Platform, as well as for executives and IT decision makers evaluating the Google Cloud Platform. This course introduces participants, through a combination of presentations, demos, and hands-on labs, to the extensive data capabilities of the Google Cloud Platform, and a detailed view of its data processing and machine learning capabilities. Students taking this course should have basic proficiency with a common query language such as SQL, experience with data modeling, extraction, transformation, and load activities, experience developing applications using a common programming language, and a familiarity with machine learning or statistics.

Course objectives:

  • Identify the purpose and value of the essential Big Data and Machine Learning products in the Google Cloud Platform
  • Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to the Google Cloud Platform
  • Employ BigQuery and Cloud Datalab to carry out interactive data analysis.
  • Train and use a neural network using TensorFlow

Python for Machine Learning

Python for Machine Learning is designed for experienced Python developers looking to understand and create a wide variety of machine learning algorithms to predict classes, continuous values, and much more. This course focuses on SciKit Learn to learn all aspects of machine learning ranging from a variety of regression types (Linear / Lasso /Ridge), Elastic Net, K Nearest Neighbors and Means Clustering, Hierarchal Clustering, DBSCAN, PCA, and Model Deployment.

Course objectives:

  • You will learn how to use data science and machine learning with Python
  • Understand Machine Learning from top to bottom
  • Learn NumPy for numerical processing with Python
  • Conduct feature engineering on real-world case studies

Learning about AI and ML can be an exciting and fascinating journey. AI is a rapidly growing field that is already revolutionizing many aspects of our lives, from healthcare to transportation to finance. By implementing ML and process automation, you can make your business more responsive and productive.

No matter where you are in your AI and ML journey, we've got training to help you adopt best practices to move your business forward; check out United Training's Artificial Intelligence training courses here to begin your AI journey.

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