TGViewer
Machine Learning & Artificial Intelligence | Data Science Free Courses Machine Learning & Artificial Intelligence | Data Science Free Courses @datasciencefree · 68.7K subscribers
Post #1121 3.24K
Complete Roadmap to become a data scientist in 5 months

Free Resources to learn Data Science: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D

Week 1-2: Fundamentals
- Day 1-3: Introduction to Data Science, its applications, and roles.
- Day 4-7: Brush up on Python programming.
- Day 8-10: Learn basic statistics and probability.

Week 3-4: Data Manipulation and Visualization
- Day 11-15: Pandas for data manipulation.
- Day 16-20: Data visualization with Matplotlib and Seaborn.

Week 5-6: Machine Learning Foundations
- Day 21-25: Introduction to scikit-learn.
- Day 26-30: Linear regression and logistic regression.

Work on Data Science Projects: https://t.me/pythonspecialist/29

Week 7-8: Advanced Machine Learning
- Day 31-35: Decision trees and random forests.
- Day 36-40: Clustering (K-Means, DBSCAN) and dimensionality reduction.

Week 9-10: Deep Learning
- Day 41-45: Basics of Neural Networks and TensorFlow/Keras.
- Day 46-50: Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).

Week 11-12: Data Engineering
- Day 51-55: Learn about SQL and databases.
- Day 56-60: Data preprocessing and cleaning.

Week 13-14: Model Evaluation and Optimization
- Day 61-65: Cross-validation, hyperparameter tuning.
- Day 66-70: Evaluation metrics (accuracy, precision, recall, F1-score).

Week 15-16: Big Data and Tools
- Day 71-75: Introduction to big data technologies (Hadoop, Spark).
- Day 76-80: Basics of cloud computing (AWS, GCP, Azure).

Week 17-18: Deployment and Production
- Day 81-85: Model deployment with Flask or FastAPI.
- Day 86-90: Containerization with Docker, cloud deployment (AWS, Heroku).

Week 19-20: Specialization
- Day 91-95: NLP or Computer Vision, based on your interests.

Week 21-22: Projects and Portfolios
- Day 96-100: Work on personal data science projects.

Week 23-24: Soft Skills and Networking
- Day 101-105: Improve communication and presentation skills.
- Day 106-110: Attend online data science meetups or forums.

Week 25-26: Interview Preparation
- Day 111-115: Practice coding interviews on platforms like LeetCode.
- Day 116-120: Review your projects and be ready to discuss them.

Week 27-28: Apply for Jobs
- Day 121-125: Start applying for entry-level data scientist positions.

Week 29-30: Interviews
- Day 126-130: Attend interviews, practice whiteboard problems.

Week 31-32: Continuous Learning
- Day 131-135: Stay updated with the latest trends in data science.

Week 33-34: Accepting Offers
- Day 136-140: Evaluate job offers and negotiate if necessary.

Week 35-36: Settling In
- Day 141-150: Start your new data science job, adapt to the team, and continue learning on the job.

ENJOY LEARNING 👍👍
  • 👍 6
  • ❤ 1
  • 🤣 1
More from @datasciencefree
  1. Oct 14, 2026⚡️ Kandinsky 6.0 Video vs Competitors: Benchmark Analysis The flagship of the new open-sou…
  2. Sep 27, 2026Machine Learning Roadmap | |-- Fundamentals | |-- Mathematics | | |-- Linear Algebra | | |…
  3. Sep 24, 2026🚀 𝐁𝐞𝐜𝐨𝐦𝐞 𝐚𝐧 𝐀𝐈 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐢𝐧 𝟐𝟎𝟐𝟔 🎯 Choose Your Learning Track: 💻…
  4. Sep 23, 2026Machine Learning Roadmap
  5. Sep 23, 2026SQL & Python Cheatsheet for Beginners ❤️
  6. Sep 22, 2026#Ad #AI_Models 🔥 GigaChat 3.5 Reasoning [Open-Source] ℹ️ Overview: New LLM that thinks be…
Threads Profile ViewerView any public Threads profile without an account.Open ThreadLook →Writing with AI? Make it sound human.Metric37 rewrites AI drafts so they read naturally. Free AI detector, 1,500 words free.Try Metric37 →