For each programme, write down:
Type: skills-focused / long-form online / credential-linked / short
Total duration: ______
Weekly hours expected: ______
Live sessions per week: ______
Credential received: ______  Issued by: ______
Classroom option: yes / no
Source of each fact: (document or email, with date)

Match programme type to your goal
Goal: first data job in months, hands-on proof  → skills-focused training
Goal: deep, structured learning while working   → long-form online (check hours)
Goal: formal credential for a specific need       → credential-linked (check issuer)
Goal: learn one missing tool                      → short course

weekly_free_hours = 10        # be honest
programmes = {
    "Option A": {"weekly_hours": 0, "months": 0},   # fill from written evidence
    "Option B": {"weekly_hours": 0, "months": 0},
}
for name, p in programmes.items():
    if p["weekly_hours"] == 0:
        print(name, "- ask for expected weekly hours")
    elif p["weekly_hours"] > weekly_free_hours:
        print(name, "- needs more time than you have; risky")
    else:
        print(name, f"- fits; about {p['weekly_hours'] * p['months'] * 4} total hours")

Life calendar check (next 6-12 months)
Work peaks / exams: ______________
Family events: ______________
Travel: ______________
Will the programme's schedule survive these? Yes / No
If No, prefer batch-based training with repeat options or flexible deadlines.

# A project that shows depth handles imbalance and explains trade-offs
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import classification_report

X, y = make_classification(n_samples=5000, weights=[0.95, 0.05], random_state=42)
X_tr, X_te, y_tr, y_te = train_test_split(X, y, stratify=y, random_state=42)
for cw in [None, "balanced"]:
    m = LogisticRegression(max_iter=1000, class_weight=cw).fit(X_tr, y_tr)
    print("class_weight =", cw)
    print(classification_report(y_te, m.predict(X_te), digits=3))

Ask both providers:
1. How many graded coding assignments are there?
2. Who reviews projects, and what feedback do I get?
3. How quickly are doubts answered?
4. Are mock interviews included? How many?
5. What happens if I need to pause or repeat?
6. What career support is included, in writing?

Weighted Scorecard (1-5 from evidence)
Criterion            Weight   Uncodemy   upGrad
Fits my weekly time    3        ___        ___
Hands-on depth         3        ___        ___
Project review         3        ___        ___
Credential need met    2        ___        ___
Support                2        ___        ___
Interview preparation  2        ___        ___
Total cost clarity     1        ___        ___
Set weights before scoring.

Evidence Log
Provider: ______
Documents received: syllabus / schedule / fee sheet / project brief
Key facts with dates:
1.
2.
3.
Open questions: ______

Decision Note
Chosen: ______
Why:
1.
2.
Risks and how I will manage them:
______________
First month plan: Python + statistics basics