AI Learning Path for Novice

Learning AI by Doing It

As a person who does not have a perfect background on Mathematics and Basic Science, learning AI is somewhat challenging. However, AI is not a new kid on the block. If you want to start to learn AI by today, you shall find numerous things to learn and it will become complicated. On this article, I want to share about how to learn AI with the minimum effort at the beginning and then increasing based on your need. I split the steps into three major steps: Level 1 (Fundamental), Level 2 (Associate), and Level 3 (Expert). As a case study, I use Microsoft ecosystem to start the learning process. Let's get started.

Level 1 Fundamental

Start to learn what is AI all about. Think the AI as a solution rather than a set of mechanism / process. On this level, you should learn what AI impact in the society. On this level, you will learn AI as a black box that empower you to do more.

• You can start by understanding the AI on Azure. If you want to learn how AI is applied in the cloud computing.
• After you grab the fundamental, try to explore which one do you find most interested to understand.
  • If you interest with image / audio / visual, you can start learning how to use AI on computer vision
  • If you interest with speech / text / understand the meaning, you can start learning how to use AI on natural language processing
  • If you interest with chatbot, you can start learning how to use AI on chatbot
• Enriching your knowledge about the AI in this MOOC Course

After you grab the fundamental knowledge my recommendation is to join AI-900 exam to validate your knowledge.

Level 2 Associate

On this level, you will learn how to develop customized AI solution based on the 'existing' model. You will need

• Microsoft Cognitive Services. It is a set of services that can be extended to provide a set of AI service.
• Azure Machine Learning Studio. It is a tool to design, develop, and deploy the AI solution.

You can start the learning process by

• Understanding the role and the benefit of cognitive services.
  • Azure Cognitive Language Services
  • Azure Cognitive Speech Services
  • Azure Vision Services
  • Azure Decisions
  • Azure Search
• Creating a model with Azure Machine Learning Studio by learning this course to learn
  • Try to build the classification model
  • Try to build the clustering model
  • Try to build the regression model

After this course, you can join AI-100 exam to validate your knowledge as AI engineer

Level 3 Expert

On this level, you will learn custom development of AI solution based on the 'niche' problems that need you to build the model from the scratch. You will need

• Visual Studio / Visual Studio Codes.
• SQL Server / Azure Data Lake / Azure Storage or any data solution that can help you to build and to maintain your model.

You can start the learning process by

• Understanding the option to build machine learning
• Choosing the right tools
  • If your computer is not sufficient you can try the Data Science Virtual Machine
  • If your computer is good enough you can build the AI Solution with AI tools with Visual Studio
    • Learn ML.NET if you are .NET developer, I recommend you to use Visual Studio 2019 or newer.
    • Learn Python if you are non .NET developer, I recommend you to use Visual Studio Codes.

There is a lot of option to learn after this. For example, you can learn how Deep learning, AI on IOT, AI works on data analytics, how to use ML Flow in Databricks, or using R as your choice of your programming language. After this course, my recommendation is to visit Azure Architecture Center to understand the recommended architecture to build better solution.

You can learn further by clicking the links.