Start Data Analytics from Zero: Cisco’s Free Data Analytics Essentials Course and Eight Prompts That Make AI Your Personal Coach

I am a data analytics beginner enrolled in Cisco Data Analytics Essentials (estimated 30 hours, covering Excel, then SQL, then Tableau and a final project).

My time: [number] hours per week, and I want to finish in [number] weeks.
My background: [e.g. basic Excel, no SQL].

Create a weekly plan as a table: week | modules | hours | extra exercise outside the course | how I know I have mastered it.
Add a review day every two weeks and suggest a mini project after finishing each tool (Excel, SQL, Tableau).
If the timeline is unrealistic for my time, say so and suggest a better one.

You are a patient Excel coach. Do not give me the final answer to the exercise.

What I am trying to do: [describe the task, e.g. extract the year from a date column and average the rating per year]
My columns: [column names and type of each]
What I tried: [the formula or step and the error]

Deliver:
1. The logic step by step in words.
2. Which functions or tools fit (e.g. XLOOKUP, SUMIFS, PivotTable) and why.
3. A worked example on small, different data you create.
4. A similar challenge for me to solve; then correct my answer when I send it.

You are a data analyst specialising in data quality.

Dataset: [description]
Columns: [name: type: example value] for each column
Approximate rows: [number]
Analysis goal: [the question I want to answer]

Create an ordered cleaning checklist:
1. The check (missing values, duplicates, mixed date formats, extra spaces, outliers, inconsistent categories).
2. Which columns specifically.
3. How to detect it in Excel (function or tool).
4. How to fix it, and when deleting would be a mistake.
5. What to record in my cleaning log.

Remind me to keep an untouched original copy.

You are a SQL coach. Explain; do not shortcut.

Schema:
[table (columns)] for each table, and relationships: [e.g. movies.id = ratings.movie_id]

The question: [e.g. top 10 highest-rated films after 2010 with more than 1000 ratings]
My current query (if any):
[paste]
Error message: [if any]

Deliver:
1. Turn the question into logical steps (which table, filter, grouping, ordering).
2. Build the query gradually, explaining each part (SELECT, JOIN, WHERE, GROUP BY, HAVING, ORDER BY).
3. If I have an error: its exact cause and how to avoid it.
4. A slightly harder follow-up question to practise.

This is the schema I practise on:
[tables, columns and relationships]

Create 10 graded SQL exercises:
- 1-3: SELECT, WHERE, ORDER BY.
- 4-6: GROUP BY, aggregates, HAVING.
- 7-8: JOINs across two or more tables.
- 9-10: subqueries or window functions.

For each: a practical business question (not SQL wording) and a difficulty level.
Do not write the solutions. I will send my query for each; correct it, explain any mistake and suggest a cleaner version.

You are a dashboard designer skilled in data storytelling.

Data: [column descriptions]
Audience: [who uses it and what decision they make]
Core message: [...]

Design the dashboard on paper:
1. 3-5 questions the dashboard answers.
2. For each: the right chart type, why it beats alternatives, and the fields used.
3. Layout order (most to least important) and interactive filters.
4. A title for each chart that states the insight, not the variable name.
5. Five common design mistakes to avoid in this specific dashboard.

Write a professional README.md for a data analytics project on GitHub, using only this information:

- Project title: [...]
- Analytical question: [...]
- Data source and size: [...]
- Cleaning steps I did: [...]
- Tools: [Excel / SQL / Tableau]
- Top 3 findings (with the numbers I found): [...]
- Tableau Public link, if any: [...]
- Limitations: [...]

Sections: Overview, Question, Data, Method, Key findings, How to reproduce, Limitations and next steps.
Write clearly for a recruiter with two minutes, and add no finding I did not provide.

Act as a recruiter for a [junior data analyst / intern] role.

My skills: Excel, basic SQL, Tableau, and an analysis project on [topic].

Run a mock interview:
- One question per message; wait for my answer.
- Mix: a behavioural question, a practical SQL question, a chart-choice question, a question about my project, and one about handling messy data.
- After each answer: a score out of 5, what was good, and how to make it stronger.
- After 8 questions: a summary of my strengths and what to improve before the real interview.