
In this lecture you take the first lesson of your own course apart stage by stage, you see the stage everybody underestimates, and you leave with a range and a reserve you can plan with instead of one hopeful weekend.
This course is built from six disciplines: audience research, learning design, course production, training craft, AI in learning and marketing channels.
The map of the course
A dictionary for reading lectures recorded for other audiences as course work
Three questions to ask after every lecture
A short self-diagnostic that shows which sections to watch first
Download the First Lesson Build Estimate and fill in one line after each lecture.
What a survey answers, and the questions it will never answer
The most common study types, and what each is good for
Automation tools
Market benchmarks worth comparing against
Satisfaction, loyalty and engagement studies
Experience studies and value proposition studies
Short pulse studies, and when short beats thorough
The rest of the catalogue
Question types, and how the type changes the answer
Scales, response options and questionnaire length
Open questions: worth the cost of analysing them or not
Platforms, and building a questionnaire from scratch
Setting the task before writing a single question
Design that does not exhaust the respondent
Promoting the questionnaire like a small campaign
Reminders that work without irritating anybody
Report formats, and which chart types earn their space
Which sections actually get read
Analysing open answers and free text
Writing recommendations rather than observations
What conclusions the data supports, and what it does not
Planning actions against the findings
Interim studies to check whether anything moved
The competency model behind the profession
How adults learn, and what follows from that
The training plan and the ADDIE model
Assessing need, types of training, and the six disciplines of breakthrough learning
Shaping the end goal before designing anything
Linking learning objectives to a result somebody can see
The basic types of learning result
Mapping the learner journey, and the diagnostic checklist
What training consists of, and what affects the outcome
Preparation before the learning
The process itself
Transferring it into practice, and the design checklist
How learning works, and its key steps
The nine steps, and the bottlenecks between them
The importance of repetition
Success factors, motivation, and the learning value chain
Transfer into real work as the actual measure of value
The main obstacles to putting knowledge into practice
Sixteen factors that decide whether it happens
The power of reminders
Why support after the course matters more than the course
How performance support works, and the options available
The purpose of a coach
The role of feedback, and the support checklist
Why evaluate at all, and how to justify the benefit
Types of evidence, and the problems with each
Six steps of the evaluation process
How to report the result to whoever is paying
The difference between training somebody and developing them
Development techniques
Career development
Working with high-potential and high-performing people
What developing people means at the level of a whole organisation
Change management
The learning organisation model, and knowledge management inside it
Developing leaders, and succession planning
Linking learning to the wider strategy
Connecting it to the systems around it
Automation of learning, and online delivery
Gamification of learning
What separates online formats from traditional ones
Learning theory, and how adults take in information
The principles that make material stick
How a full programme gets built
Working principles for the technology
The toolkit you actually need
Choosing technology you will not regret
What makes production move faster
Choosing a topic and shaping a programme
Sources of material when you are not the only expert
Questions, assignments and intensive design
Practices that raise usefulness, and developing your own expertise
How to behave on camera, and how to work a live audience
Stages of the participant life cycle, and how you behave in each
Preparation, launch and the opening session
Starting the discussion rather than waiting for it
Tracking what landed
Teaching application rather than recall
Feedback, cases and reflection
Closing and debriefing
Managing the programme once it is live
Progress monitoring, and how to challenge participants
Checking the work that comes back
What makes a course genuinely useful rather than merely finished
Structure, content, style, support and challenge as five separate jobs
Dale's cone, and why telling people things sits at the bottom of it
The formats that exist on the market
Types of training, and how effectiveness gets evaluated
The first beat of the cycle: problematisation
Everything that happens before anybody arrives
The optimal number of participants
Why breaks matter more than they look, and how to design the programme
Visual material, and the timetable of a session
The working styles a trainer can adopt
Reflection, conceptualisation and practice as three distinct beats
A model for building a training design from scratch
This course contains the use of artificial intelligence.
Most courses that fail were invented alone. The topic was chosen because the author knew it well, and the first real person appeared after everything was already recorded.
By the time you find out what people wanted, re-recording is out of the question
That is the whole problem, and it happens in a specific order. You pick a subject you are good at. You write an outline of what you consider important. You record fifteen lessons over two months. Then you launch, and the questions people ask turn out to be about something adjacent that you covered in nine minutes near the end. Now you are choosing between shipping a course that misses, and starting again. Nobody starts again.
What this course covers
Forty lessons in the order the work actually happens, beginning before the outline exists. Research first: what a study can tell you and what it cannot, the types and what each is good for, question design and how the type of question changes the answer, scales and length, whether open questions repay the analysis, fielding the questionnaire like a small campaign, the report, analysing free text, and turning findings into a concept. Then the learning science: how adults take in information, ADDIE, setting the end result before the outline, mapping the learner journey, what a piece of learning is made of, the nine steps and the bottlenecks between them, the importance of repetition, sixteen factors that decide whether knowledge reaches real work, the power of reminders, performance support after the last lesson, evaluation in six steps, and the difference between training somebody and developing them. Then building the course: what changes online, the platform and production stack, programme and material, sources when you are not the only expert, assignments and intensive design, behaviour on camera, the participant life cycle, holding attention to the end, and evaluating both the people and the course. Then the craft of teaching a group: Dale's cone, problematisation, group size, the four-beat cycle, group dynamics and norms, resistance, facilitation against moderation, metaphors, the five rules for sub-groups, how to end, and running a webinar so it is not a broadcast. Then production with AI: the platforms, course generation, materials, video and tests, adapting one piece of material to several learning styles, personalised paths and analytics. Finally the launch: the course site as an entry point, referrals as an organic channel, email, search, video and copy, paid promotion and remarketing, each social platform on its own terms, and the numbers that tell you whether the launch worked.
Three blocks were recorded for a workplace audience
I would rather say this before you meet it in lesson three. The research block was recorded around employee studies, so its catalogue of study types is internal — but the craft of a questionnaire is the same craft: a scale is a scale, a leading question is a leading question, and free-text analysis does not care who answered. The learning science block is a course for someone running a learning function, and six of its ten lessons speak about organisations; the other four describe how a human being absorbs and applies something, and without those this course would be production advice. The channel block was recorded around employer marketing, so the mechanics are general and the examples come from hiring.
Who is teaching this
I am Mike. I built the people system at Preply as it became a unicorn, and I have worked at Wargaming, iDeals and Alfa-Bank. More than 1.6 million students have enrolled in my courses across 185 countries, and over 150,000 specialists have gone through my programmes. I hold PHRi and SHRM-CP certifications and represent HRCI in more than ten countries.
What is included
Lifetime access to all 40 lessons
Active instructor support in the Q&A section
A Udemy Certificate of Completion
Working material: the questionnaire design guide, the diagnostic and design checklists, the nine steps of learning, the sixteen transfer factors, the four-beat session model, the five rules for sub-groups, the AI production stack, and the launch channel plan
The research stage, which most course-creation programmes skip entirely
Where to start
Write your course title as a question your audience would actually type. Then ask twenty of them whether that is the question they have. Enrol now and start today.