Udemy – 21 Data Science Portfolio Projects in 21 Days
English | Tutorial | Size: 6.25 GB
Master Machine Learning & AI: From Time Series Analysis to Reinforcement Learning with Real-World Applications
This comprehensive data science course is structured as an intensive 21-day journey through the most relevant and in-demand areas of machine learning and artificial intelligence. Each day focuses on a complete project implementation, carefully designed to build both your technical skills and your professional portfolio.
The curriculum progresses logically from foundational concepts to advanced applications:
**Week 1 (Days 1-7):**
– Begin with time series forecasting using ARIMA
– Master customer analytics and segmentation
– Develop credit risk models
– Build social media sentiment analyzers
– Create e-commerce recommendation systems
– Design employee attrition predictors
– Implement real estate pricing models
**Week 2 (Days 8-14):**
– Develop cybersecurity threat detection systems
– Create fraud detection algorithms
– Build energy consumption forecasting models
– Design traffic flow prediction systems
– Calculate customer lifetime value
– Analyze stock market patterns
– Implement NLP text classification
**Week 3 (Days 15-21):**
– Conduct market basket analysis
– Create health risk prediction models
– Build music genre classifiers
– Forecast housing market trends
– Develop automated trading systems
– Master demand forecasting with Prophet
– Build AI agents using reinforcement learning
Each project utilizes industry-standard tools and frameworks including:
– Python programming language
– Popular libraries like Scikit-learn, TensorFlow, and PyTorch
– Data manipulation tools like Pandas and NumPy
– Visualization libraries including Matplotlib and Seaborn
– Advanced ML frameworks such as Prophet and NLTK
The course includes:
– On-demand video content
– Downloadable source code for all projects
– Real-world datasets for practical experience
– Interactive coding exercises
– Project-based assessments
– Certificate of completion
All materials reflect the latest industry practices and technological advances in the field of data science and machine learning.
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