Some training sessions are quickly forgotten. Others stick with people for months, even years. The difference rarely comes down to the topic. It comes down to the design.
At Data Society, we build learning experiences that shift both mindset and skillset. Our AI literacy training, data science courses, and business intelligence development programs are designed not just to inform, but to transform. Instructor-led training plays a critical role in that process.
“There is no way to do skill building in our view without actually modeling flexible thinking,” says Michael Harwick, Director of Learning Design at Data Society. “We want to help build the soft skills on the back end that also feel necessary to accomplish this work.”
Today’s workforce doesn’t just need information. They need context, confidence, and a safe environment to apply what they have learned. Instructor-led training makes this possible, especially when upskilling on complex topics such as AI, data, and analytics.
Why Instructor-Led Training Still Works
The demand for fast and scalable learning has prompted many organizations to adopt asynchronous, self-paced courses. However, while on-demand content offers flexibility, it often falls short when the goal is behavior change or problem-solving.
At Data Society, instructor-led training remains a core delivery model, particularly for AI literacy courses and data science training.
“We’re firmly committed to instructor-led training,” Harwick explains. “We don’t develop many asynchronous products. While we work hard to standardize the teaching experience across several different instructors, we are also firmly committed to letting them riff when they need.”
This ability to adapt in the moment is especially valuable for technical topics. It allows instructors to meet learners where they are and guide them through areas of confusion, misalignment, or hesitation.
“There’s strong value in letting real learners with real problems address a real expert and pick their brain,” Harwick says. “And if that is what’s going to ultimately produce the kind of learning outcome that we need in conjunction with our material, then we want to be able to empower people to take advantage of that relationship.”
When AI Feels Intimidating, People Shut Down
As organizations roll out AI literacy training for the first time, many employees feel overwhelmed or uncertain. Tools like ChatGPT or Copilot may feel intuitive for some, but others worry about doing it “wrong” or making poor decisions based on unclear outputs.
This is where instructor-led training becomes critical. When delivered live, whether in person or virtually, it allows learners to ask questions, test assumptions, and contextualize their knowledge through dialogue.
“We always start with principles, continue with demonstration, and end with application. That’s just what works. It’s how people remember things,” Harwick explains.
This method is particularly effective for learners who are new to data science tools or AI concepts. In a well-structured AI literacy course, the focus is not solely on theory, but on creating a safe space for experimentation and conversation.
Worked Examples and Empowered Thinking
At the heart of Data Society’s approach is a blend of structured progression and practical examples.
“We start with scaffolded, gradual release of responsibility,” Harwick says. “And we use focused lessons and worked examples.”
These examples walk learners through step-by-step solutions, helping them see how problems are broken down and solved in the real world.
“We’re willing to hit fast forward on an example if it helps the learning process,” Harwick says, “but we will probably ask you to do it more step-by-step in an exercise.”
This model balances observation with action. It encourages learners to reason through unfamiliar scenarios and recognize patterns. These skills are especially valuable in business intelligence development programs and data science courses where critical thinking is often more important than memorizing syntax.
Confidence Is a Learning Outcome
Skill building is only part of the goal. Identity building matters too.
“We want people to be able to say, ‘I do data,’ or ‘I do AI,’” Harwick says. “Sometimes all it takes is introducing someone to Stack Overflow and saying, ‘You can Google this. There’s a whole community out there for you to plug into.’ It’s a weird light bulb moment, but it’s so empowering.”
That moment of empowerment changes everything. When learners begin to believe that they belong in the world of AI or data, they become more curious and less hesitant. They engage more deeply, ask better questions, and retain what they learn.
This shift is what distinguishes high-impact training. Whether part of an AI literacy course or a broader upskilling program, instructor-led design helps unlock mindset change that outlasts the session itself.
Designing for Clarity and Business Value
In addition to modeling and mindset, Harwick emphasizes the importance of guiding learners through a clear learning arc.
“We want to give learners a road map of where we’re going versus what we’re learning in the moment,” he says. “When you’re dealing with technical skills or complex tool stacks, it can get really easy to just get in the weeds.”
That clarity helps learners stay grounded, especially when learners encounter unfamiliar topics . It also helps connect tactical learning to business value, an essential bridge in business intelligence development and AI literacy training.
In data science courses designed for business users, this clarity often helps cross-functional teams align around what’s possible, what’s useful, and how to move forward together.
When to Choose Instructor-Led Training
Instructor-led training is especially valuable when:
– The subject matter is complex or evolving (like AI or data science)
– Your audience is non-technical or mixed-experience
– The organization is launching a broader upskilling program
– Collaboration, Q&A, or real-time problem solving are key outcomes
Virtual instructor-led training is also practical when designed well. With the proper structure and facilitation, VILT offers the same benefits as in-person sessions, with more flexibility for distributed teams.
Want to deliver training that builds both skill and confidence?
Data Society designs instructor-led and virtual instructor led training for data and AI literacy, business intelligence development, and technical upskilling. Whether you’re planning your next data science course or rolling out an AI literacy training initiative, we can help your team learn, grow, and apply. Request a consultation today!
FAQs: Instructor-Led Training for AI and Data
Practical AI literacy courses combine live instruction, real-world examples, and time for reflection and application. They are designed to build confidence and support collaboration across roles.
