Prepare for applications

What you will be able to do

Know, for a specific job, which requirements your evidence covers and which it does not, and prepare for the interview that the role really uses. Then you apply with a clear story instead of a hope.

Before you startWhat to know and to have readyAbout 35 minutes

What you need to know

• The two-minute walkthrough and the decision story, from Explain decisions: The two-minute walkthrough.
• How to link each claim to evidence, from Portfolio anatomy: Link every claim to evidence.

What you need

• One real job advertisement for your primary role, with its text saved in your ai-career folder. You can use one of the advertisements that you read in step 4 of Choose a realistic route: Guided practice: your choice.
• Your evidence: ## Inventory with evidence from Evidence over self-ratings: Guided practice: update your inventory, and ## Project briefs from Portfolio anatomy: Guided practice: two project briefs.
• Your study week, under ## My study week, from Plan deliberate practice: Guided practice: plan your next week. You add interview practice to it.

Read the advertisement as a list of claims to prove

Most advertisements have two lists: required (“you have”, “must”) and preferred (“nice to have”, “a plus”). Employers often write the advertisement for an ideal person who does not exist. Many people who are hired do not match every line.

A useful rule: apply when your evidence covers most of the required list, and you can explain how you are closing the rest. Do not wait for every line.

For each requirement, find your evidence and rate it:

• Strong: a project, work result or diagnostic task that shows it directly.
• Partial: related evidence, or a course in progress.
• None: no evidence yet.

Worked example: Daniela maps an advertisement

Six months into her plan, Daniela finds this fictional advertisement:

AI Product Analyst, Finance Automation. Required: experience in accounts payable or financial operations; ability to define requirements and success measures for automation tools; SQL or Python for data analysis; clear communication with finance teams. Preferred: experience evaluating AI or ML outputs; familiarity with language models.

Requirement	My evidence	Strength
Accounts payable experience	7 years in accounts. Wrote the invoice checking procedure.	Strong
Requirements and success measures	Project brief for the invoice checker, with a baseline and success measure. Led the accounting system move.	Strong
SQL or Python for analysis	Invoice checker script. Python final assignment.	Strong for Python. None for SQL.
Communication with finance teams	Monthly reports to the finance director. Trains new staff.	Strong
Preferred: evaluating AI outputs	Evaluation in my README. Evaluating AI systems is in my plan for next quarter.	Partial
Preferred: language models	The LLM course finished last month.	Partial

The required list is covered. Daniela applies. In her application, she writes one honest line about the gap: “I use Python for data analysis. I am learning SQL now, in the SQL and data course.”

Notice that her strongest rows are domain rows. Her years in accounts are the reason that she is a good candidate for this job, not an obstacle.

The kinds of interview

Different roles test different things. Find out which kinds your target role uses, from the advertisement, from the company’s careers page, or from people who work there.

Kind of interview	What happens	Common for
Experience and decisions	“Tell me about a project. Why did you choose that?”	Every role
Coding	Write or explain code, often while you talk.	AI, ML and data engineers. Data scientists.
SQL and data	Write queries, or find problems in a dataset.	Data analysts, data scientists, data engineers
Problem framing (case)	“Our support team wants AI. How do you start?”	Product managers, data scientists, solution architects
Evaluation exercise	Judge a set of AI outputs, and explain which errors matter most.	Evaluation specialists, AI product roles, SMEs
System design	Draw how the parts of a system fit together.	AI and ML engineers, solution architects
Take-home task	A small project at home, then a discussion of your choices.	Many roles

You have practised several of these in this course. Problem framing was Module 3. Decision stories were the last lesson. The evaluation exercise is close to the work of Priya and Grace in Module 1.

A practice plan for interviews

Interview skill is like every other skill: it grows with practice and feedback, not with reading. Add a small, regular block to your study plan:

• Every week, 30 minutes: one practice question of the kind that your role uses. Say or write your answer before you look at any example.
• Every two weeks: your two-minute walkthrough, aloud, to a person, with their questions afterwards.
• Before each real interview: read the advertisement again, and prepare one decision story for each strong row of your map.

A word about certificates

This platform gives a certificate when you complete a course. A certificate shows that you completed the lessons. It is honest about that, and anybody can check it on its verification page. But no certificate guarantees a job. Employers hire people for what they can show and explain. Use the certificate next to your projects, never instead of them.

Guided practice: map your advertisement

1. In notes.md, add a heading: ## Job map.
2. From your saved advertisement, copy each required and preferred item into a table like Daniela’s.
3. For each item, write your evidence and its strength: strong, partial or none.
4. Count the required items with strong evidence. Write: “Apply now” or “Apply after …”, with the reason.
5. Write which kinds of interview this role probably uses, and one practice question for each.
6. Add a 30-minute weekly interview practice block to your study plan.

Check: every “strong” rating names a specific piece of evidence that you could show or describe in an interview.

Independent variation: find a second advertisement for your adjacent option, and map it in the same way. Compare the two maps: which one is closer today?

Common mistake

Waiting until you match everything

Symptom: you read advertisements every week, but you do not apply, because each one has a line that you do not match. Months pass.

Cause: you treat the advertisement as a list that you must match completely. Most employers do not expect that.

Fix: map the advertisement. If your evidence covers most of the required items, apply, and write one honest line about how you are closing the main gap. An interview also gives you feedback that no course can give.

Check your understanding

Daniela has no SQL evidence, but she applies. Why is this reasonable, and how does she handle the gap?

Show the answer

The requirement says “SQL or Python”, and she has strong Python evidence, so the requirement is met. The other required items are strong. She handles the SQL gap honestly: one line in her application that she is learning it now, in a named course. That is a specific plan, not an empty promise.

Check your understanding

Which kind of interview from the table have you already practised in this course, and where?

Show the answer

Problem framing, in Module 3, where you framed the ticket project and wrote a project brief. Experience and decisions, in the last lesson, with decision stories and a walkthrough. Also a small evaluation exercise: judging results and errors, as Priya and Grace did in Module 1, and the diagnostic tasks in Module 2.

Recap

• Treat each requirement as a claim to prove, and map it to evidence: strong, partial or none.
• Apply when most required items are strong, with one honest line about the main gap.
• Find out which kinds of interview your role uses, and practise them every week.
• A certificate shows completion. Projects and explanations get jobs.

Next, you bring the whole course together in your career transition brief.

Next: Final assignment