Data Science Roadmap - Advanced

Follow this step-by-step roadmap to master data_science at Advanced level

1

Advanced Machine Learning

4 weeks

▹Ensemble Methods (Bagging, Boosting, Random Forest, XGBoost)
▹Feature Importance
▹Dimensionality Reduction (PCA, t-SNE)
▹Hyperparameter Tuning (GridSearch, RandomSearch)
▹Mini-Project: Predicting House Prices

2

Deep Learning

5 weeks

▹Neural Networks Basics
▹TensorFlow & Keras
▹CNNs (Image Classification)
▹RNNs & LSTMs (Sequence Data)
▹Transfer Learning
▹Mini-Project: Image Classifier with CNN

3

Natural Language Processing (NLP)

4 weeks

▹Text Preprocessing (Tokenization, Stopwords, Lemmatization)
▹Bag of Words & TF-IDF
▹Word Embeddings (Word2Vec, GloVe, BERT)
▹Sentiment Analysis
▹Text Classification
▹Mini-Project: Twitter Sentiment Analysis

4

Big Data & Cloud

4 weeks

▹Big Data Concepts
▹Hadoop & Spark Basics
▹Data Pipelines (Airflow, Kafka)
▹Cloud Platforms (AWS, GCP, Azure)
▹Mini-Project: Spark Data Analysis

5

Deployment & MLOps

3 weeks

▹Model Serialization (Pickle, Joblib)
▹Flask/FastAPI for Model Deployment
▹Dockerizing ML Models
▹CI/CD for ML
▹Monitoring & Retraining
▹Mini-Project: ML Model Deployment on Cloud

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