🛣️ Data Scientist Complete Roadmap

1. Foundation Stage (Basic Knowledge)

🔹 Mathematics & Statistics

• Probability, Permutation & Combination
• Descriptive Statistics (Mean, Median, Mode, Variance, SD)
• Inferential Statistics (Hypothesis Testing, p-value, ANOVA, t-test, Chi-square test)
• Linear Algebra (Vectors, Matrices, Eigenvalues, Eigenvectors)
• Calculus basics (Derivatives, Gradients, Partial Derivatives)

🔹 Programming Basics

• Python (Numpy, Pandas, Matplotlib, Seaborn)
• R (Optional but useful)
• SQL (Data Querying, Joins, Aggregation, Window Functions)

2. Data Handling & Analysis

🔹 Data Collection

• APIs, Web Scraping, Databases

🔹 Data Cleaning & Preprocessing

• Handling Missing Values
• Outlier Detection
• Data Transformation & Scaling
• Feature Engineering

🔹 Exploratory Data Analysis (EDA)

• Data Visualization (Histograms, Boxplots, Scatterplots)
• Correlation & Covariance
• Finding Patterns

3. Core Machine Learning (ML)

🔹 Supervised Learning

• Linear Regression, Logistic Regression
• Decision Trees, Random Forest
• Gradient Boosting (XGBoost, LightGBM, CatBoost)
• Support Vector Machine (SVM)

🔹 Unsupervised Learning

• K-Means Clustering
• Hierarchical Clustering
• PCA (Dimensionality Reduction)

🔹 Model Evaluation

• Train-Test Split, Cross Validation
• Accuracy, Precision, Recall, F1-score
• ROC Curve, AUC

4. Advanced Machine Learning & Deep Learning

🔹 Neural Networks

• Basics of ANN
• Backpropagation, Activation Functions

🔹 Deep Learning Frameworks

• TensorFlow, Keras, PyTorch

🔹 Specialized Areas

• Natural Language Processing (NLP) → Text Classification, Sentiment Analysis, Transformers
• Computer Vision (CV) → CNN, Image Classification, Object Detection
• Time Series Forecasting

5. Big Data & Cloud

• Hadoop, Spark (Big Data Processing)
• Cloud Platforms → AWS, Azure, GCP
• Databricks

6. Tools & Deployment

• Git & GitHub (Version Control)
• Docker & Kubernetes (Containerization)
• Streamlit / Flask / FastAPI (Model Deployment)
• MLflow (Model Tracking)

7. Business & Communication Skills

• Problem-Solving Mindset
• Data Storytelling (Turning Data into Insights)
• Creating Dashboards (Power BI, Tableau)
• Writing Reports & Presentations

8. Projects & Portfolio Building

✅ Sample Projects Ideas:

• Customer Churn Prediction
• Movie Recommendation System
• Sentiment Analysis of Tweets
• Fraud Detection
• Sales Forecasting with Time Series
• Image Classification (Cats vs Dogs, Medical Imaging)

👉 Upload projects on GitHub + Kaggle + LinkedIn Portfolio.

9. Research & Specialization (Optional but Valuable)

• Read & Publish Research Papers
• Focus on specific domains: Healthcare, Finance, Marketing, Public Health

10. Job Preparation

• Leetcode / HackerRank → Practice SQL + Python Problems
• Kaggle Competitions → Hands-on Problem Solving
• Mock Interviews & Resume Preparation
• Networking (LinkedIn, Conferences, Seminars)