Codeayan AI Data Science Resources

🚀 Embarking on the journey to become a Data Scientist? Here’s a roadmap that breaks down every milestone — from mastering the basics to deploying real-world models. Whether you’re a beginner or refining your skills, this visual guide helps you stay focused and inspired. 💡 Remember: Data science isn’t just about algorithms — it’s about curiosity, creativity, and continuous learning. #DataScience #MachineLearning #AI #CareerGrowth #LearningJourney #Python #Analytics #DataVisualization #MLOps #LinkedInLearning @LinkedInLearning Entri Kaggle @Shruthi M

🤖 Top 5 Scikit-learn Codes Every Data Scientist Should Know Building a Machine Learning model doesn’t have to be complicated—if you know the right steps. With Scikit-learn, you can go from raw data to predictions in just a few lines of code. 📌 What you’ll learn: • Loading datasets • Splitting data (train/test) • Training ML models • Making predictions • Evaluating performance 💡 Mastering these fundamentals is the first step toward becoming a confident Data Scientist. Start simple. Stay consistent. Build real projects. #MachineLearning #DataScience #Python #ScikitLearn #AI #Coding #LearnToCode #TechSkills

This image captures data science in its most honest form: not a single skill, but a layered synthesis of thinking, tools, and context. It shows that knowing statistics alone is just theory, and coding alone is just execution—but when combined with models and real-world understanding, they transform into true intelligence that can solve meaningful problems. The quiet truth here is that data science is less about algorithms and more about connecting knowledge to impact. #DataScience #MachineLearning #Analytics #AI #Python

Day 5 of my Machine Learning Journey 🚀 Today I worked on one of the most important concepts in data preprocessing — Encoding & Feature Scaling. 🔹 Converted categorical data into numerical using LabelEncoder 🔹 Applied Standardization using StandardScaler 🔹 Applied Normalization using MinMaxScaler 🔹 Practiced on multiple datasets (COVID, Tips, Insurance) Understanding how to properly prepare data is crucial before applying any ML model. This step directly impacts model performance. Learning step by step and building strong fundamentals 💪 #MachineLearning #DataScience #Python #LearningJourney #DataPreprocessing #AspiringDataScientist

Day 26 of My AI & Data Science Journey Today I learned about Lists in Python and explored various list methods that make data handling easier. 🔹 append() – Add elements to a list 🔹 insert() – Insert element at a specific position 🔹 remove() – Remove an element 🔹 pop() – Remove element using index 🔹 sort() – Sort the list 🔹 reverse() – Reverse the list 💡 Key takeaway: Lists are powerful for storing and manipulating data, and understanding their methods helps in writing efficient and clean code. Practiced small exercises to strengthen my understanding. #Python #DataScience #CodingJourney #LearningEveryday #AI

Breaking down Machine Learning models doesn’t have to be complicated. I created this carousel to simplify 11 key ML algorithms — from fundamentals to real-world applications, including the math and Python behind them. Whether you're preparing for interviews, building projects, or transitioning into data science, this is a solid reference to keep handy. From Linear Regression → XGBoost → PCA, everything in one place. Swipe through and tell me: 👉 Which model do you use the most? #MachineLearning #DataScience #AI #Python #Analytics #DeepLearning #MLModels #DataAnalytics #TechCareer #ComputationalChemistry #ChemistryAI #LearnInPublic #CareerGrowth #AIinScience #PortfolioProject

If you’re interested in building end-to-end ML systems but don’t have MLOps experience yet, this might be useful: Timur Bikmukhametov, PhD is hosting a free 3-day hands-on bootcamp where he walks through building a real-world ML system step by step. He’ll be coding live, so you can follow the full process and see how everything fits together in practice. Could be a good starting point if you want to move beyond individual models and understand full ML workflows. More details: https://lnkd.in/d6ZZCm2q #machinelearning #datascience #mlops #ai #python #analytics

🏆Excited to share my latest work on Machine Learning & Al Practicals! I've created a collection of hands-on Jupyter Notebooks covering core ML concepts and algorithms as part of my academic learning journey. This project helped me strengthen my understanding by implementing models from scratch and analyzing real datasets. Key topics covered: DataFrame Operations Correlation Matrix Normal Distribution Simple Linear Regression Logistic Regression Decision Trees (ID3 Algorithm) Confusion Matrix Decision Tree Pruning Tools & Technologies: Python | Pandas | NumPy | Scikit-learn | Matplotlib | Jupyter Notebook Through this project, I gained practical experience in: Data preprocessing Model building & evaluation Data visualization Understanding ML algorithms in depth Check out my GitHub repository: https://lnkd.in/gJCenmxd I'm continuously learning and exploring more in the field of AI & ML. Open to feedback and suggestions! #Machine Learning #ArtificialIntelligence #DataScience #Python #LearningJourney #GitHub #Students #AI #ML

AI is no longer just a buzzword — it's reshaping how we build and scale systems. From automating workflows to enabling real-time decision-making, tools like Python, Snowflake, and Databricks are at the centre of this transformation. In my recent work, I’ve seen how integrating data pipelines with AI models can significantly improve efficiency and reduce manual effort. #AI #Python #DataEngineering #MachineLearning #Innovation

Great evolution visual! The real unlock with Agentic RAG isn’t just better answers, it’s data sovereignty. When your reasoning agent controls which sources, tools, and knowledge graphs it queries, you can finally keep sensitive data within your own infrastructure rather than routing everything through external APIs. Self-evaluation loops also mean you can enforce compliance boundaries at inference time, not just at ingestion. The architecture that reasons is also the architecture you can govern.