Complete roadmap to learn data science in 2024 👇👇

1. Learn the Basics:
- Brush up on your mathematics, especially statistics.
- Familiarize yourself with programming languages like Python or R.
- Understand basic concepts in databases and data manipulation.

2. Programming Proficiency:
- Develop strong programming skills, particularly in Python or R.
- Learn data manipulation libraries (e.g., Pandas) and visualization tools (e.g., Matplotlib, Seaborn).

3. Statistics and Mathematics:
- Deepen your understanding of statistical concepts.
- Explore linear algebra and calculus, especially for machine learning.

4. Data Exploration and Preprocessing:
- Practice exploratory data analysis (EDA) techniques.
- Learn how to handle missing data and outliers.

5. Machine Learning Fundamentals:
- Understand basic machine learning algorithms (e.g., linear regression, decision trees).
- Learn how to evaluate model performance.

6. Advanced Machine Learning:
- Dive into more complex algorithms (e.g., SVM, neural networks).
- Explore ensemble methods and deep learning.

7. Big Data Technologies:
- Familiarize yourself with big data tools like Apache Hadoop and Spark.
- Learn distributed computing concepts.

8. Feature Engineering and Selection:
- Master techniques for creating and selecting relevant features in your data.

9. Model Deployment:
- Understand how to deploy machine learning models to production.
- Explore containerization and cloud services.

10. Version Control and Collaboration:
- Use version control systems like Git.
- Collaborate with others using platforms like GitHub.

11. Stay Updated:
- Keep up with the latest developments in data science and machine learning.
- Participate in online communities, read research papers, and attend conferences.

12. Build a Portfolio:
- Showcase your projects on platforms like GitHub.
- Develop a portfolio demonstrating your skills and expertise.

Best Resources to learn Data Science

Intro to Data Analytics by Udacity

Machine Learning course by Google

Machine Learning with Python

Data Science Interview Questions

Data Science Project ideas

Data Science: Linear Regression Course by Harvard

Machine Learning Interview Questions

Free Datasets for Projects

Please give us credits while sharing: -> https://t.iss.one/free4unow_backup

ENJOY LEARNING 👍👍

The reason you're not feeling motivated is because you don't have a clear goal.

You do have a goal, but it's only that you want to make a lot of money. With just that, you'll only experience FOMO (fear of missing out), not money.

Hard work is your responsibility, but you need to set small and immediate goals. For example, if you're studying DSA, it's not something you can complete in one day. A goal for now should be to master one topic thoroughly until you can solve all medium-level questions, and slowly, you'll crack it.

This is crucial at every stage of life.

Motivation will come when you start achieving small things, and eventually, everything will fall into place one day. ♥️

Use cases of top programming languages

Mastery in programming is not about increasing code complexity. It is about solving increasingly complex problems with simple code.

sql.pdf

Resume Tips for Freshers 😄❤️

TCS SQL Interview Questions

Algorithms
Jeff Erickson, 2019