Data Science for Beginners With free resources
Following is the roadmap to learn Data Science skills for a total beginner (no coding or computer science background needed). It includes FREE learning resources for technical skills (or tool skills) and soft (or core) skills.
Total Duration: 6 Months
3 hours in Tool Skills + 1 hour in Core Skills = 4 hours study Every Day
Week 1 , 2 :
Python
Lists, Dictionaries, Tuples
Read, Write files
Exception handling
Object & Classes
Assignment
- Finish all these exercises Click hare
- Create a professional looking LinkedIn profile.
- Upload a Clear photo in linkedIn
Week 3 , 4 :
Pandas, Data Visualization (matplotlib)
Numpy
- Numpy YouTube Playlist
- Another Numpy Playlist
Pandas
- Pandas YouTube playlist (first 10 videos only)
Matplotlib or seaborn
- Do not learn both
- Matplotlib and seaborn are libraries for data visualization and exploration
- Matplotlib YouTube playlist
Core/Soft Skills
- Start following prominent data science, analytics influencers
- Example: Daliana Liu , Hemanand Vadivel
Increase engagement
- Start commenting meaningfully on data science and career related
posts - Helps network with others working in the industry build
connections - Learning and brainstorming opportunity
- Remember online presence is a new form of resume
Business Fundamentals – Soft Skill
- Learn business concepts from ThinkSchool and other YT Case Studies
- Example: How Amul beat competition
Discord
- Start asking questions and get help from the community. This post shows
how to ask questions the right way Click Hare - Join codebasics discord server
Assignment
- Write meaningful comments on at least 10 data science related LinkedIn posts
- Note down your key learnings from 3 case studies on ThinkSchool and share with
your friend
Week 5 , 6 , 7 , 8 :
Statistics and Math for Data Science
Statistics and probability
- Finish this excellent Khan academy course on statistics and probability.
- When you are doing khan academy course, you can use stat quest YouTube channel to
clear your doubts. - Complete math and statistics for data science YouTube playlist with Python code (Khan
academy course doesn’t have Python code)
Assignment
- Finish all exercises in that playlist
- Perform EDA (Exploratory data analysis on at least 3 datasets on www.kaggle.com
Week 9 , 10 , 11 , 12 :
Machine Learning
Machine Learning
Topics
- Feature engineering
- Regression
- Classification
- Clustering
Learning Resources
- Youtube Playlist (First 21 videos)
- Feature engineering playlist
Core/Soft Skills
Project Management
- Scrum: scrumtrainingseries.com
- Kanban: Youtube Playlist
- Tools: JIRA, Notion
Assignment
- Complete all exercises in ML playlist
- Work on 2 Kaggle ML notebooks
- Write 2 LinkedIn posts on whatever you have learnt in ML
- Discord: Help people with at least 10 answers
Week 13 , 14 , 15 :
Machine Learning Projects with Deployment
Projects
Project
- You need to finish two end to end ML projects. One on Regression, the other on
Classification . - Regression Project: Bangalore property price prediction YouTube playlist .
Project covers following
- Data cleaning
- Feature engineering
- Model building and hyper parameter tuning
- Write flask server as a web backend
- Building website for price prediction
- Deployment to AWS
Classification Project: Sports celebrity image classification
- YouTube playlist
- Project covers following:
1. Data collection and data cleaning
2. Feature engineering and model training
3. Flask server as a web backend
4. Building website and deployment
Assignment
- In above two projects make following changes
☐ Use FastAPI instead of flask. FastAPI tutorial
☐ Regression project: Instead of property prediction, take any other project of
your interest from Kaggle for regression
☐ Classification project: Instead of sports celebrity classification, take any other
project of your interest from Kaggle for classification and build end to end
solution along with deployment to AWS or Azure
Week 16 , 17 :
SQL
SQL
Topics:
- Basics of relational databases
- Basic Queries: SELECT, WHERE LIKE, DISTINCT, BETWEEN, GROUP BY, ORDER BY
- Advanced Queries: CTE, Subqueries, Window Functions
- Joins: Left, Right, Inner, Full
- Stored procedures and functions
- No need to learn database creation, indexes, triggers etc. as those things arerarely used by data scientists
Learning Resources (pick only one course)
Core/Soft Skills
Presentation skills
- Death by PowerPoint Youtube Playlist
Assignment
Participate in resume project challenge on codebasics.io
- These challenges help you improve technical skills, soft skills and business understanding Click Hare
Make a LinkedIn post with a submission of your resume project challenge
- Semple post
- Codebasics is promoting winning entries to employers. This way you can get interview calls. We do this in two ways
- We have a database of employers hiring for data analyst positions. We send first 10 or 20 profiles based on their performance .
- LinkedIn post by Dhaval (who has more than 100k followers and some of them are HR managers, data analytics senior managers): Click Hare
Week 18 , 19 , 20 :
BI Tool (Power BI or Tableau)
Power BI
Free resources
- Sales insights Power BI project
- Personal finance project : Project Link
- HR data analytics project : Project Link
Tableau
Tabeau
- Codebasics sales insights project : Project Link
- HINDI codebasics sales insights project : Project Link
Should I learn Power BI or Tableau?
- If someone asks me to pick between Power BI and Tableau, I always suggest Power BI as it is growing in popularity as compared to Tableau.
- This Gartner research shows Power BI is leading a BI game: Click Hare
Assignment
Participate in one resume project challenge
- These challenges help you improve technical skills, soft skills and business understanding
Make a LinkedIn post with video presentation
- Example post (Naveen s)
Discord server participation
Week 21 , 22 , 23 , 24 :
Deep Learning
Deep Learning
- Deep Learning YouTube playlist
- End-to-end potato disease classification project
Assignment
- Instead of potato plant images use tomato plant images or some other image classification dataset
- Deploy to Azure instead of GCP
- Create a presentation as if you are presenting to stakeholders and upload video presentation on LinkedIn
Week 25 :
onwards
Final Work
- More projects
- Online brand building through LinkedIn, Kaggle, Discord, Opensource contribution
- Resume and interview preparation Video link
- Job application and Success ….
Extra :
Tips of effective learning
Tips of effective learning
Spend less time in consuming information, more time in
- Digesting
- Implementing
- Sharing
Group learning
- Use partner-and-group-finder channel on codebasics discord server for group
study and hold each other accountable for the progress of your study plan. Here
is the discord server link.
Inspirational Stories
- Career transition stories.
Advance Tipic
ML Ops. What is it and how can I learn it?
- This post has necessary information
Cloud ML Platforms
- Big cloud service providers such as AWS, Azure, Google Cloud have their own ML offering such as Amazon Sagemaker in case of AWS. As a fresher it is ok if you are not familiar with these cloud platforms but once you have some experience it is good to have experience and know-how of at least one cloud ML platform.
Natural Language Processing (NLP)
- NLP YouTube playlist
Computer Vision
- Computer vision is a vast field where one can use OpenCV, PyTorch, Tensorflow etc for deep learning approaches for computer vision as well. You can find many resources online on this. I do not have a specific recommendation for this.