How can you use hands-on training to teach AI skills to non-technical staff?

2 Choose the right tools and data

The next step is to select the tools and data that will support your learning objectives. Depending on the topic and the level of your learners, you may want to use different platforms, frameworks, or libraries for AI. For example, you could use Google Colab, TensorFlow, or PyTorch for machine learning, or NLTK, spaCy, or Hugging Face for natural language processing. You also need to choose the data sets that are relevant, realistic, and accessible for your learners. You can use public data sources, such as Kaggle or UCI, or create your own data sets from your business domain.

3 Design the hands-on activities

The third step is to design the hands-on activities that will engage your learners and help them practice the AI skills. You can use different formats, such as exercises, projects, or games, depending on the time and the complexity of the topic. The key is to make the activities interactive, challenging, and fun. You can also provide feedback, hints, or solutions to guide your learners and reinforce their learning. For example, you could ask your learners to analyze a data set, build a machine learning model, or generate a summary from a text.

4 Prepare the materials and resources

The fourth step is to prepare the materials and resources that will support your hands-on training session. You need to create or collect the content that will explain the concepts, methods, and examples of AI. You can use slides, videos, articles, or books, depending on the preference and the background of your learners. You also need to provide the code, data, and instructions that will enable your learners to perform the hands-on activities. You can use notebooks, scripts, or web applications, depending on the tools and the data that you have chosen.

5 Deliver the hands-on training session

The fifth step is to deliver the hands-on training session to your learners. You need to set up the environment, such as the computers, the internet, and the software, that will allow your learners to access the tools and the data. You also need to facilitate the learning process, such as introducing the topic, explaining the concepts, demonstrating the examples, and monitoring the activities. You can use different methods, such as lectures, demonstrations, discussions, or quizzes, depending on the format and the size of your session.

6 Evaluate the learning outcomes

The final step is to evaluate the learning outcomes of your hands-on training session. You need to measure how well your learners have achieved the learning objectives that you have defined. You can use different methods, such as tests, surveys, or interviews, depending on the criteria and the feedback that you want to collect. You also need to reflect on how you can improve your hands-on training session for future learners. You can use different methods, such as self-assessment, peer review, or mentorship, depending on the strengths and the weaknesses that you want to address.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?