Best Big Data Path for a Diploma Holder Starting From Zero

Month 1 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review goals for the day
9:00 AM — Deep work (3 hours)
   - Week 1: Python basics
   - Week 2: SQL fundamentals
   - Week 3: Linux and CLI
   - Week 4: Data basics with Pandas
12:00 PM — Lunch break
1:00 PM — Practice (coding challenges, SQL exercises)
2:00 PM — Deep work (2 hours)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Exercise, rest
8:00 PM — Read data engineering blogs (30 min)
10:00 PM — Wind down

Week 1 Review:
□ Can I write functions and loops in Python?
□ Do I understand lists and dictionaries?
□ Have I solved 10 small exercises?

Week 2 Review:
□ Can I write SELECT and WHERE clauses?
□ Can I join two tables?
□ Have I written 20 SQL queries?

Week 3 Review:
□ Can I navigate the terminal confidently?
□ Do I understand file permissions?
□ Can I write a small bash script?

Week 4 Review:
□ Can I load a CSV in Pandas?
□ Can I clean missing values?
□ Have I built a small analysis notebook?

Month 2 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review goals for the day
9:00 AM — Deep work (3 hours)
   - Week 5: Hadoop and HDFS
   - Week 6: Apache Spark fundamentals
   - Week 7: Spark SQL and DataFrames
   - Week 8: Data pipelines with Spark
12:00 PM — Lunch break
1:00 PM — Practice (Spark jobs on sample data)
2:00 PM — Deep work (2 hours)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Exercise, rest
8:00 PM — Read Spark docs / tutorials (30 min)
10:00 PM — Wind down

Week 5 Review:
□ Do I understand what HDFS is?
□ Can I explain MapReduce in simple words?
□ Have I run a simple Hadoop job?

Week 6 Review:
□ Do I understand what Spark is?
□ Can I create a DataFrame in PySpark?
□ Have I run a transformation and action?

Week 7 Review:
□ Can I write Spark SQL queries?
□ Do I understand joins in Spark?
□ Have I processed a bigger dataset?

Week 8 Review:
□ Can I build a simple ETL pipeline?
□ Is it documented in a notebook?
□ Have I pushed it to GitHub?

Month 3 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review goals for the day
9:00 AM — Deep work (3 hours)
   - Week 9: Kafka and streaming basics
   - Week 10: Cloud basics and managed Spark
   - Week 11: Portfolio project
   - Week 12: Applications and interviews
12:00 PM — Lunch break
1:00 PM — Networking and practice
2:00 PM — Deep work (2 hours)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Exercise, rest
8:00 PM — Interview prep (30 min)
10:00 PM — Wind down

Week 9 Review:
□ Do I understand what Kafka is?
□ Can I write a producer and consumer?
□ Have I streamed events end to end?

Week 10 Review:
□ Can I run a job on a cloud platform?
□ Do I understand cloud storage basics?
□ Have I secured credentials properly?

Week 11 Review:
□ Is my portfolio project complete?
□ Is it documented end to end?
□ Is it on GitHub with a clear README?

Week 12 Review:
□ Is my resume focused on big data?
□ Have I sent 25 quality applications?
□ Have I practiced mock interviews?

Daily Tracker:
Date: _________
☐ Morning routine completed
☐ Deep work session 1 (3 hours)
☐ Deep work session 2 (2 hours)
☐ Practice exercises completed
☐ Project work done
☐ Exercise completed
☐ Reviewed progress
☐ Planned tomorrow

Today's Accomplishments:
1. 
2. 
3. 

Tomorrow's Priorities:
1. 
2. 
3. 

Weekly Tracker:
Week: _____ (Month 1 / 2 / 3)

Goals for this week:
1. 
2. 
3. 

Daily Progress:
Mon: ☐☐☐
Tue: ☐☐☐
Wed: ☐☐☐
Thu: ☐☐☐
Fri: ☐☐☐
Sat: ☐☐☐
Sun: ☐☐☐

Weekly Wins:
1. 
2. 
3. 

Challenges & Solutions:
1. 
2. 

Next Week's Goals:
1. 
2. 
3. 

Monthly Tracker:
Month: _____ (1 / 2 / 3)

Monthly Goal:
_______________________________________________

Week 1 Progress: ☐☐☐
Week 2 Progress: ☐☐☐
Week 3 Progress: ☐☐☐
Week 4 Progress: ☐☐☐

Monthly Wins:
1. 
2. 
3. 

Skills Gained:
1. 
2. 
3. 

Portfolio Items:
1. 
2. 
3. 

Applications Sent: _____
Interviews: _____
Offers: _____

Next Month's Goal:
_______________________________________________