Data Science Roadmap
Data Science
Following is the roadmap to learning Data scientist skills for a total beginner. It includes learning resources for technical skills (or tool skills) and soft (or core) skills Prerequisites: You must have skills or interests to build skills in Coding and Math. Without these two you cannot become an Data scientist.
Data Scientist Tool skills
- Python
- SQL
- DSA&Git and Github
- Pandas&EDA
- Machine Learning
- Deep Learning
- NLP or computer vision
- ML Ops
Data Scientist core skills
- Computer Science Fundamentals
- Math and statistics
- Communication
- Business understanding
Computer Science Fundamentals
- Data representation: Bits and Bytes, Storing text and numbers, Binary number system.
- Basics of computer networks, IP addresses, Internet routing protocol.
- UDP, TCP, HTTP, and The World Wide Web
- Programming basics: variables, strings, and numbers, if condition, loops
- Algorithm basics
Chapter 1 Introduction to Python
- Print, comments, variables
- Type casting and strings
- Indexing, slicing
- Operators and conditional statements
- Exception handling
- Regular expressions
Chapter 2 Python Libraries
- Numpy
- Pandas
- Matplotlib & Seaborn
Chapter 3 Math Fundamentals
- Math functions
- Loops in Python
- Nested if-else
- Nested loops
- Functions (inbuilt & user-defined)
- Data structures
Chapter 4 File Handling & SQL
- Fundamentals of classes
- File handling
- SQL introduction
- HackerRank problems & assignments
- LeetCode problems
- Data cleaning
Chapter 5 Advanced SQL
- Database constraints
- Normalization
- CRUD operations
- Advanced queries
- Views, transactions
- SQL practice sets
- Stored procedures
- Window functions
- Common Table Expressions (CTE)
- SQL logic for complex problems
- Scenario-based SQL questions
Chapter 6 Excel and VBA
- Excel functions and formulas
- VBA introduction
- Macro recording and usage
- VBA procedures and loops
- Dashboard creation
Chapter 7 Power BI
- Introduction to Power BI
- Basic charts and visualization
- Advanced chart types
- Data modeling
- Connecting to different data sources
- M Language and DAX functions
- AI integration in Power BI
- Case studies
Chapter 8 R Language
- Fundamentals of R
- Data structures in R
- Data visualization with R
- Packages like stringr and dplyr
- Case studies in R
Chapter 9 Data Visualization Tools
- Amazon QuickSight
- Google Data Studio
- Case studies and dashboard creation
Chapter 10 Fundamentals of AI
- Vectors, matrices
- Linear equations and calculus
- Probability and statistics
- AI applications in real world scenarios
Chapter 11 Data Structures & Algorithms
- Time complexity
- Sorting algorithms
- Data structures like linked lists, stacks, queues, trees, and graphs
- Dynamic programming
Chapter 12 Machine Learning
- Introduction to ML
- Feature engineering and selection
- Regression analysis
- Classification algorithms
- Clustering techniques
- Dimensionality reduction
- Model evaluation and deployment
Chapter 13 Deep Learning
- Neural network fundamentals
- TensorFlow and PyTorch basics
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- Natural Language Processing (NLP)
- Time series analysis with neural networks
Chapter 14 Git & GitHub
- Version control basics
- Git commands and workflows
- Collaborative development using GitHub
Chapter 15 Kaggle Optimization Course
- Utilizing Kaggle for portfolio building
- Dataset exploration, competitions, and notebooks
- Medals and portfolio boosting techniques
Core Skills and Job Preparation
Create a professional-looking LinkedIn profile Linkedin ▪ Start following prominent AI influencers
Increase engagement
- Start commenting meaningfully on AI 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
Discord
Start asking questions and get help from the community
This post shows how to ask questions the right way: https://bit.ly/3I70EbI
Core/Soft Skills
- Project Management
- Scrum:
- https://scrumtrainingseries.com/
- Kanban
- https://youtu.be/jf0tlbt9lx0
- Tools: JIRA, Notion
ATS Resume Preparation
- Resumes are dying but not dead yet. Focus more on online presence.
- Here is the resume tips video along with some templates you can use for your data analyst resume:
- https://www.youtube.com/watch?v=buQSI8NLOMw
- Use this checklist to ensure you have the right ATS Resume
Portfolio Building Resources
You need a portfolio website in 2024. You can build your portfolio by using these free resources.
GitHub
Upload your projects with code on github and using github.io create a portfolio website
Sample portfolio website:
Linktree
Helpful to add multiple links in one page.
- ATS friendly resume preparation
- Linkedin optimization
- Certificate of course completion
- Online community access where jobs are posted
- Interview Questions and answers
- Bootcamp project
- Resume & Project Related
Documents