Beginner's Guide · Version Control & ML Tools

Git and GitHub or PyTorch First? What Beginners Should Pick

AK Ankit Kaushik · Lead Trainer, Data Engineering & AI | Updated 28 August 2026 | 18 min read Free · Career Guide

A 90-day learning path — Month 1: Git & GitHub, Month 2: PyTorch Basics, Month 3: PyTorch Advanced.

Quick summary — Git/GitHub or PyTorch first?

Start with Git and GitHub if you want to build good habits early. This guide breaks down every day, week, and month of your learning journey — with checklists, goals, and tracking to keep you on course.

In this guide you will learn:

Month 1: Git & GitHub — daily and weekly learning plan.
Month 2: PyTorch Basics — daily and weekly learning plan.
Month 3: PyTorch Advanced — daily and weekly learning plan.
Tracking templates — track your progress.
Accountability tips — stay on track.

SECTION 01Month 1: Git & GitHub (Days 1-30)

The first month is about building your version control foundation. Here's your weekly learning plan:

Week	Focus	Daily Actions	Weekly Goal
Week 1	Git Basics	Install Git, init, add, commit, status, log	Create your first repository
Week 2	Branching & Merging	Branch, checkout, merge, resolve conflicts	Merge a feature branch
Week 3	GitHub	Remotes, push, pull, pull requests, issues	Push a project to GitHub
Week 4	Collaboration Workflow	Fork, clone, PR review, .gitignore	Contribute to an open-source repo

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: Git init, add, commit, log
   - Week 2: Branching and merging
   - Week 3: GitHub remotes and pull requests
   - Week 4: Open-source collaboration
12:00 PM — Lunch break
1:00 PM — Practice (commit, branch, merge)
2:00 PM — Deep work (2 hours)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Exercise, rest
8:00 PM — Read Git documentation (30 min)
10:00 PM — Wind down

Week 1 Review:
□ Can I init a repo, add, and commit?
□ Do I understand the staging area?
□ Have I viewed my commit history?

Week 2 Review:
□ Can I create and switch branches?
□ Can I merge branches?
□ Have I resolved a merge conflict?

Week 3 Review:
□ Can I push to GitHub?
□ Can I open a pull request?
□ Do I understand remotes?

Week 4 Review:
□ Can I fork and clone a repo?
□ Have I made a pull request to an open-source project?
□ Do I know how to use .gitignore?

month1-planner.md

Key insight: Month 1 is about building good habits. Git and GitHub are used in every ML project — learn them before PyTorch so you can version your models and datasets from day one.

SECTION 02Month 2: PyTorch Basics (Days 31-60)

The second month is about learning PyTorch — tensors, autograd, and your first neural network. Here's your weekly learning plan:

Week	Focus	Daily Actions	Weekly Goal
Week 5	Tensors	Tensor creation, operations, GPU, numpy bridge	Manipulate tensors confidently
Week 6	Autograd & Optimization	Gradients, loss functions, optimizers	Train a simple linear model
Week 7	Neural Networks	nn.Module, layers, activation, forward pass	Build a feedforward network
Week 8	Build Project 1	End-to-end training pipeline	Complete Project 1

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: Tensors and operations
   - Week 6: Autograd and optimizers
   - Week 7: Neural network modules
   - Week 8: Project 1
12:00 PM — Lunch break
1:00 PM — Practice (Kaggle, small datasets)
2:00 PM — Deep work (2 hours)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Exercise, rest
8:00 PM — Read PyTorch documentation (30 min)
10:00 PM — Wind down

Week 5 Review:
□ Can I create and manipulate tensors?
□ Do I understand GPU vs CPU?
□ Can I convert between numpy and tensors?

Week 6 Review:
□ Do I understand gradients?
□ Can I use an optimizer?
□ Have I trained a linear model?

Week 7 Review:
□ Can I build an nn.Module?
□ Do I understand forward and backward passes?
□ Have I built a feedforward network?

Week 8 Review:
□ Is Project 1 complete?
□ Is it documented?
□ Is it on GitHub?

month2-planner.md

Key insight: Month 2 is about building evidence. Projects speak louder than resumes — focus on quality and documentation.

SECTION 03Month 3: PyTorch Advanced (Days 61-90)

The third month is about CNNs, RNNs, transfer learning, and landing interviews. Here's your weekly learning plan:

Week	Focus	Daily Actions	Weekly Goal
Week 9	CNNs	Conv2d, pooling, image classification	Train an image classifier
Week 10	Transfer Learning	Pretrained models, fine-tuning, data augmentation	Fine-tune a pretrained model
Week 11	Build Project 2	End-to-end deep learning project	Complete Project 2
Week 12	Interview Prep & Apply	Mock interviews, applications, follow-ups	Apply to 20+ roles

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: CNNs
   - Week 10: Transfer learning
   - Week 11: Project 2
   - Week 12: Interview prep & applications
12:00 PM — Lunch break
1:00 PM — Practice (Kaggle competitions)
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 Conv2d and pooling?
□ Have I trained an image classifier?
□ Do I understand batch size and epochs?

Week 10 Review:
□ Can I load a pretrained model?
□ Can I fine-tune it on my own data?
□ Do I understand data augmentation?

Week 11 Review:
□ Is Project 2 complete?
□ Does it use a real dataset?
□ Is it on GitHub?

Week 12 Review:
□ Have I done mock interviews?
□ Have I applied to 20+ roles?
□ Have I followed up?

month3-planner.md

Key insight: Month 3 is about execution. CNNs and transfer learning are what most ML job interviews focus on — build projects that prove you can use them.

SECTION 04Tracking templates

Use these templates to track your 90-day progress:

Daily Tracker:
Date: _________
☐ Morning routine completed
☐ Deep work session 1 (3 hours)
☐ Deep work session 2 (2 hours)
☐ Practice exercises completed
☐ Project work completed
☐ 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:
_______________________________________________

tracking-templates.md

SECTION 05Accountability tips

Here are tips to stay accountable during your 90-day learning journey:

Find an accountability partner — share your weekly goals with someone who will check in.
Track daily wins — write down 3 wins each day, no matter how small.
Join a community — connect with others learning Git or PyTorch.
Celebrate milestones — reward yourself at 30, 60, and 90 days.
Review weekly — every Sunday, review your progress and plan the week ahead.

Pro tip: Consistency beats intensity. Even 2-3 hours of focused work daily is enough to complete this 90-day learning plan.

SECTION 06Interview Q&A — Git & PyTorch

Q1Should I learn Git or PyTorch first?

Start with Git and GitHub. Version control is a foundational skill you'll use in every PyTorch project — and it's easier to learn without the complexity of deep learning.

Q2Do I need Git to learn PyTorch?

Technically no — but in practice, yes. Every serious ML project uses version control. Learning Git first lets you version your models, datasets, and experiments from day one.

Q3Can I learn both at the same time?

Yes — but focus on Git first. It's simpler and takes less time. Once you're comfortable with Git, move to PyTorch.

Q4What if I already know Python?

Great — you can move faster through the PyTorch sections. But still learn Git first. It's a small investment that pays off immediately.

Q5What if I get a job before 90 days?

Congratulations! Use the remaining time to prepare for your new role or continue building skills. The plan is flexible.

SECTION 07Test yourself — Git vs PyTorch quiz

Five questions. No sign-up.

0 / 5

Pick an answer to see why it is right or wrong.

SECTION 08Frequently asked questions

What's the most important month in the 90-day Git & PyTorch plan?

All months are important, but Month 1 (Git & GitHub) is critical because it sets the foundation for everything that follows.

How much time should I commit daily?

5-6 hours of focused work daily is optimal. If you have less time, even 2-3 hours consistently can work — you'll just need to extend the timeline.

What if I don't have a portfolio?

Build one in Month 2. Start with 2-3 projects — it doesn't need to be perfect, just real and well-documented.

Can I combine months?

Yes — if you have more time, you can combine activities. For example, you can start learning PyTorch while finishing Git practice.

What if I'm not applying in Month 3?

Use the extra time to build more projects, improve your portfolio, or practice more interview questions. Stay ready.

What I would do in the first 30 daysLayoff · 14 min Why sending 500 resumes won't workJob Search · 14 min Rebuild your resume for the AI job marketResume · 15 min Which skills to learn before applyingSkills · 14 min 90-day career recovery roadmapRecovery · 16 min How AI can help you prepare for interviewsAI · 11 min

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Complete 90-day learning path
Skills & projects
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Git and GitHub or PyTorch First? What Beginners Should Pick

Git and GitHub or PyTorch First? What Beginners Should Pick

Quick summary — Git/GitHub or PyTorch first?

SECTION 01Month 1: Git & GitHub (Days 1-30)

SECTION 02Month 2: PyTorch Basics (Days 31-60)

SECTION 03Month 3: PyTorch Advanced (Days 61-90)

SECTION 04Tracking templates

SECTION 05Accountability tips

SECTION 06Interview Q&A — Git & PyTorch

SECTION 07Test yourself — Git vs PyTorch quiz

Five questions. No sign-up.

SECTION 08Frequently asked questions

SECTION 09Related reads

Your 90-day Git & PyTorch path starts now