Data Science Advance
Programming · 20 chapters · 418 sections · about 197 hours
Chapters
20 chapters · 418 sections- 1Introduction to Advanced Data Science15 sections
- 2Data Wrangling and Feature Engineering28 sections
- 3Advanced Data Visualization Techniques23 sections
- 4Statistical Inference and Hypothesis Testing9 sections
- 5Supervised Learning – Advanced Algorithms27 sections
- 6Unsupervised Learning – Clustering & Dimensionality Reduction15 sections
- 7Ensemble Methods – Bagging, Boosting, and Stacking27 sections
- 8Deep Learning and Neural Networks23 sections
- 9Natural Language Processing (NLP)25 sections
- 10Time Series Analysis and Forecasting13 sections
- 11Recommender Systems30 sections
- 12Model Evaluation and Validation23 sections
- 13Big Data Technologies (Hadoop, Spark)31 sections
- 14Machine Learning Pipelines and Automation11 sections
- 15Cloud Computing in Data Science (AWS,Azure, GCP)10 sections
- 16Ethics and Responsible AI24 sections
- 17Case Studies and Real-World Projects10 sections
- 18Data Science for Business and Decision- Making27 sections
- 19Advanced SQL and NoSQL for Data Science25 sections
- 20Deployment and Monitoring of Machine Learning Models22 sections
About this course
Data Science, especially at an advanced level, is an interdisciplinary field focused on extracting knowledge and insights from data using various techniques and tools.