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Artificial intelligence: An overview of AI and machine learning

Alex Castrounis

Advanced analytics such as artificial intelligence and machine learning are becoming increasingly critical to developing innovative, differentiated, competitive, and successful businesses and products. AI in particular has the potential to unlock the value of data and ultimately transform businesses, industries, and human experiences.

Join Alex Castrounis for an overview of AI and machine learning fundamental concepts and processes, including common definitions, types, algorithms, processes, trade-offs, and considerations.

What you'll learn-and how you can apply it

  • Definitions of AI and machine learning, along with related concepts
  • Some of the different AI and machine learning types and algorithms
  • Common processes applied to AI and machine learning projects
  • Common tradeoffs and considerations associated with AI and machine learning

At a high-level, you will be able to:

  • Understand what AI and machine learning means
  • Understand the different types of AI and machine learning techniques and algorithms
  • Understand some of the common tradeoffs and considerations associated with AI and machine learning

This training course is for you because...

  • You're a business executive or technical practitioner interested in learning more about artificial intelligence.

Expected Outcomes: - By the end of this live, online course, you’ll understand: - AI and machine learning fundamental, concepts - Some of the different AI and machine learning types and algorithms - Common processes applied to AI and machine learning projects - Common trade-offs and considerations associated with AI and machine learning

And you’ll be able to: - Distinguish the different types of AI and machine learning techniques and algorithms and when to use them

Common Misunderstandings: 1. AI is deeply rooted in statistics, probability, mathematics, and computer science-related aspects such as programming, logic, algorithms, and so on. Given this, AI can be tricky to understand without a background in these fields if not taught with the right approach. 2. AI is a lot more hype in many ways than it is reality. People often think that AI is much more advanced than it is currently, and as such, expectations are high, and potential for disappointment is also high. 3. Many people are starting to assume that AI and machine learning is becoming more automated, or that much of it can be done ‘off the shelf’. The need for data scientists (not just software engineers that toy around with ML libraries) and experts should not be undervalued, as expertise is required to be aware of, and make decisions around critical tradeoffs, considerations, constraints, appropriate solution performance levels, and so on. Also, these experts are able to de-risk AI and ML projects and potential sunk costs, time, and effort.

About your instructor

  • Alex Castrounis founded InnoArchiTech, a company that helps businesses and people transform data into value by leveraging data science and advanced analytics techniques such as AI and machine learning. InnoArchiTech provides education, training, writing, and speaking services.

    Alex is also a book author, podcast creator and host, online course creator and instructor, writer for industry-leading publications, and public speaker.

    Before working in tech, Alex spent ten years as a race strategist, data scientist, and vehicle dynamicist for IndyCar racing teams. During his racing career, Alex competed in over 100 races worldwide, including the Indianapolis 500.

Schedule

The timeframes are only estimates and may vary according to how the class is progressing

This course is taught continuously for an hour and will consist of the topics listed below. Questions will be answered throughout the course, where possible, and time frame will be allotted at the end for Q&A.

Outline:

  • AI definitions and related concepts
  • Machine learning definition
  • Machine learning types and algorithms
  • AI types and algorithms
  • AI and machine learning processes
  • Trade-offs and considerations