Fee Comparison Sheet
                         Course A   Course B   Course C
Total fee (incl. tax)     ______     ______     ______
Live hours                ______     ______     ______
Cost per live hour        ______     ______     ______
Reviewed case studies     ______     ______     ______
Mock interviews           ______     ______     ______
Recordings / repeats      ______     ______     ______
Instalments               ______     ______     ______

Excel formulas for the fee sheet
Cost per live hour:  =IFERROR(B2/B3,"ask for hours")
Rank by value:       =RANK(B4,$B$4:$D$4,1)
Highlight best value with conditional formatting (lowest cost per hour)
Then check that the low-cost option still has reviews and case studies.

Ask the trainer during the demo:
'If two tables have duplicate customer IDs, what happens to totals after a JOIN, and how would you check for it?'

A strong answer explains:
- Duplicates multiply rows after the join
- Totals become inflated
- Check with COUNT(*) vs COUNT(DISTINCT key) before joining
- Fix by deduplicating or aggregating first

-- What a strong trainer might show
SELECT COUNT(*) AS rows_total,
       COUNT(DISTINCT customer_id) AS unique_customers
FROM customers;

-- Aggregate before joining to avoid inflated totals
SELECT c.city, SUM(o.amount) AS revenue
FROM orders o
JOIN (SELECT DISTINCT customer_id, city FROM customers) c
  ON c.customer_id = o.customer_id
GROUP BY c.city;

Review log
Source: ______  Date: ______
Mentions: ☐ SQL depth ☐ case studies ☐ trainer clarity ☐ support ☐ timings
Tone: positive / mixed / negative
Specific detail quoted in your own words: ______________
Repeated across reviews? Yes / No

import pandas as pd

# Paste review text you collected into reviews.csv (column: text)
reviews = pd.read_csv("reviews.csv")
themes = {"sql": "sql", "case study": "case stud", "doubt": "doubt",
          "trainer": "trainer", "timing": "timing", "placement": "placement"}
for theme, word in themes.items():
    count = reviews["text"].str.lower().str.contains(word).sum()
    print(f"{theme:12} {count}")

Combined Scorecard (1-5)
                      Course A   Course B   Course C
Fee value (per hour)    ___        ___        ___
Inclusions              ___        ___        ___
Faculty in demo         ___        ___        ___
Review themes           ___        ___        ___
Schedule fit            ___        ___        ___
TOTAL                   ___        ___        ___

Faculty Notes (demo class)
Trainer: ______  Topic: ______
Explained 'why'? Y / N
Used business examples? Y / N
Answered my question clearly? Y / N
Checked learners' understanding? Y / N
Overall (1-5): ___

Before paying
☐ Total fee and inclusions in writing
☐ Demo class attended
☐ Syllabus with SQL, Excel, BI, Python depth received
☐ Review themes noted
☐ Refund and batch repeat policy received
☐ Batch timing confirmed