Udemy - Data Science Innovations - Advanced Methods, Interactive ...

Files:

• Get Bonus Downloads Here.url (0.2 KB)
~Get Your Files Here ! 1. Introduction to Advanced Data Science
• 1. Introduction.html (3.0 KB)
• 10. What is Variable in the python from Basics.mp4 (49.7 MB)
• 11. Reflecting the Data Science Odyssey Milestones and Paradigm Shifts.html (0.2 KB)
• 12. Data Odyssey Unveiling Proficiency in Essential Skills & Techniques.html (0.2 KB)
• 13. Data Insights Unveiled Unraveling Real-World Challenges.html (0.2 KB)
• 14. Variable & Data Types Basic Operations with Integers, Floats, and Strings.html (0.2 KB)
• 15. Arithmetic Operations in Python.html (0.2 KB)
• 16. Python Data Structures and Syntax.html (0.2 KB)
• 17. Conditional Operations with If Statements.html (0.2 KB)
• 18. Master the art of iterating over lists, tuples, and dictionaries using both for and while loops..html (0.2 KB)
• 19. Mastering Conditional Expressions Ternary Operator.html (0.2 KB)
• 2. The Evolution of Data Science Unveiling the Historical Journey and Contemporary.html (3.6 KB)
• 20. Function Mastery & File Manipulation Parameterized Operations, Return Values, and File IO.html (0.2 KB)
• 3. Mastering Advanced Data Science Essential Skills and Techniques.html (6.5 KB)
• 4. Real-World Data Science Case Studies and Transformative Insights.html (8.2 KB)
• 5. Exploring the Data-Driven World Challenges, Opportunities, and Future Growth in.html (4.3 KB)
• 6. Foundations of Data Science Essential Concepts and Techniques for Beginners.html (10.5 KB)
• 7. Install the Jupyter-notebook in the linux from Basics.mp4 (108.3 MB)
• 7.1 Commands to install the jupyter-notebook in the linux.txt (0.9 KB)
• 8. install jupyter with python in linux with the help of pip command.mp4 (46.6 MB)
• 9. Jupyter-notebook introduction___ how to use it, how to run it from basics.mp4 (53.9 MB)
10. Ethical Considerations in Data Science
• 1. Advanced Techniques for Deploying Machine Learning Models in Production.html (11.1 KB)
• 2. Scalability and Performance Optimization for Machine Learning Models.html (5.0 KB)
• 3. Advanced Techniques for Monitoring and Maintaining Deployed Machine Learning Mod.html (8.7 KB)
• 4. Ethical Considerations in Model Deployment Ensuring Fairness, Transparency, and.html (13.1 KB)
• 5. Real-World Model Deployment Case Studies Challenges, Solutions, and Lessons.html (6.0 KB)
11. Deploying Machine Learning Models
• 1. Advanced Fraud Detection Machine Learning Techniques for Fraud Identification.html (8.0 KB)
• 2. Advanced Healthcare Analytics Predictive Modeling and Optimization for Data-Dri.html (9.0 KB)
• 3. Financial Forecasting with Data Science Time Series Analysis, Risk Assessment,.html (8.0 KB)
• 4. Advanced Techniques in Image and Video Analysis with Machine Learning.html (12.2 KB)
• 5. Genomic Data Analysis Unleashing the Power of Data Science in Genomics.html (6.4 KB)
12. Career Guidance and Job Placement
• 1. Data Science Capstone Project Kickoff Guided Initiation and Scope.html (9.9 KB)
• 2. Advanced Data Science Capstone Project Implementation.html (7.5 KB)
• 3. Data Analysis and Visualization A Comprehensive Guide for Aspiring Data Science.html (13.3 KB)
• 4. Comprehensive Capstone Project Documentation Methodologies, Findings, and Insig.html (12.2 KB)
• 5. Mastering Presentation Skills for Effective Data Science Communication.html (3.0 KB)
• 6. Data Science Capstone Project Peer Review and Feedback.html (6.4 KB)
13. Continuous Learning Opportunities
• 1. Exploring AI and Machine Learning Trends Unveiling the Future of Data Science.html (8.5 KB)
• 2. Advanced Big Data Analytics Mastering Tools and Technologies for Data Science.html (6.6 KB)
• 3. Exploring Explainable AI Enhancing Model Interpretability and Transparency.html (11.9 KB)
• 4. Edge Computing in Data Science Enhancing Real-Time Data Processing and Analytic.html (6.2 KB)
• 5. Exploring the Synergy of Quantum Computing and Data Science Algorithms, Applica.html (11.5 KB)
14. Building a Data Project Portfolio
• 1. Building a Data Science Portfolio Showcasing Your Skills and Achievements.html (10.2 KB)
• 2. Mastering Data Science Job Search Strategies Networking, Resumes, and Interview.html (9.6 KB)
• 3. Navigating Career Transitions in Data Science Specialization, Upskilling, and I.html (10.4 KB)
• 4. Industry Certifications Boost Your Data Science Career with Credibility.html (4.0 KB)
• 5. Embracing Continuous Learning in Data Science Stay Ahead of the Curve.html (3.8 KB)
15. Lifelong Learning and Growth Mindset
• 1. Emerging Technologies in Data Science Exploring the Future of AI, Machine Learn.html (6.7 KB)
• 2. Data Science in 2030 Exploring the Future of Data-driven Insights.html (11.3 KB)
• 3. Future-proofing Data Science Navigating Ethical Considerations in the Age of Da.html (4.1 KB)
• 4. Data Science for Sustainability Leveraging Data-driven Approaches for Environme.html (11.0 KB)
16. Section 15 Course Conclusion and Certification
• 1. Python Coding Challenges Enhance Your Data Science Skills with Challenging Exer.html (11.4 KB)
• 2. Python Data Manipulation Exercises Master Data Cleaning, Transformation, and An.html (9.1 KB)
• 3. Machine Learning Algorithm Practice Hands-on Coding for Data Science.html (13.5 KB)
• 4. Advanced Visualization Coding Interactive Data Visualizations with Matplotlib a.html (12.3 KB)
17. Advanced Feature Engineering
• 1. Mastering Feature Engineering Unlocking the Power of Data Insights.html (14.0 KB)
• 2. Advanced Feature Engineering Strategies Unlocking Complex Patterns in Data.html (11.2 KB)
• 3. Optimizing Model Performance The Role of Feature Engineering for Data Science P.html (10.9 KB)
• 4. Mastering Time Series Feature Engineering for Accurate Predictive Analytics.html (9.9 KB)
• 5. Ethical Considerations in Feature Engineering Bias, Fairness, and Transparency.html (7.0 KB)
18. Time Series Analysis and Forecasting
• 1. Mastering Time Series Analysis Foundations, Fundamentals, and Predictive Modeli.html (14.2 KB)
• 2. Mastering Advanced Forecasting Techniques for Enhanced Data Insights.html (8.5 KB)
• 3. Enhancing Time Series Forecasting Advanced Optimization Strategies.html (11.5 KB)
• 4. Temporal Anomaly Detection Identifying Outliers in Time Series Data.html (10.9 KB)
• 5. Real-World Applications of Time Series Forecasting Case Studies and Insights.html (8.5 KB)
19. Anomaly Detection
• 1. Unmasking Anomaly Detection Principles and Techniques.html (7.6 KB)
• 2. Advanced Fraud Detection with Anomaly Detection Techniques Strategies and Best.html (14.2 KB)
• 3. Optimizing Anomaly Detection Models Fine-Tuning for Precision.html (16.1 KB)
• 4. Temporal Anomaly Detection Monitoring Unusual Patterns Over Time.html (13.2 KB)
• 5. Beyond Security Anomaly Detection in Diverse Data Domains.html (10.4 KB)
2. Mastering Data Analysis Techniques
• 1. Advanced Statistical Analysis for Data Science Unleash the Power of Data Insigh.html (8.3 KB)
• 2. Data Science Essentials Master Descriptive Statistics for Powerful Data Analysi.html (5.2 KB)
• 3. Advanced Inferential Statistics for Data Analysis and Decision Making.html (10.1 KB)
• 4. Mastering Advanced EDA Techniques for Deeper Data Insights.html (8.8 KB)
• 5. Advanced Pattern Recognition Techniques for Data Analysis and Anomaly Detection.html (18.7 KB)
• 6. CSV File Data Reading & Loading in Python.html (0.2 KB)
20. Bayesian Methods in Data Science
• 1. Exploring Bayesian Statistics A Practical Guide for Data Scientists.html (10.7 KB)
• 2. Bayesian Inference Making Informed Decisions with Data Uncertainty.html (12.6 KB)
• 3. Optimizing Model Uncertainty Bayesian Approaches for Enhanced Predictions.html (12.9 KB)
• 4. Bayesian Machine Learning Integrating Probabilistic Models.html (5.1 KB)
• 5. Ethical Considerations in Bayesian Data Analysis Transparency and Fairness.html (9.5 KB)
21. Reinforcement Learning
• 1. Essentials of Reinforcement Learning An Introduction for Beginners.html (12.6 KB)
• 2. Reinforcement Learning Markov Decision Processes for Sequential Decision-Making.html (14.9 KB)
• 3. Deep Reinforcement Learning Navigating Sequential Decision-Making.html (4.8 KB)
• 4. Policy Gradient Methods Training Agents for Optimal Decision Strategies.html (9.1 KB)
• 5. Unlocking Success Real-World Applications of Reinforcement Learning.html (10.7 KB)
22. Big Data Analytics with Spark
• 1. code example for a data science exercise, along with enhanced features, clear ex.html (7.5 KB)
• 2. Efficient Data Processing with Spark Optimizing Large-Scale Analytics.html (10.9 KB)
• 3. Simplifying Big Data Querying and Analysis with Spark SQL and DataFrames.html (14.3 KB)
• 4. Machine Learning with Spark Harnessing Big Data for Predictive Analytics.html (4.8 KB)
• 5. Real-Time Big Data Analytics Unleashing Insights with Spark Streaming.html (6.9 KB)
23. Explainable AI (XAI)
• 1. Demystifying Explainable AI Principles and Importance.html (9.0 KB)
• 2. Interpretable Models in Machine Learning A Comprehensive Overview.html (14.6 KB)
• 3. Demystifying Black Box Models Techniques for Explainability.html (8.3 KB)
• 4. Applications of Explainable AI Real-World Impact and Success Stories.html (10.3 KB)
• 5. Ethical Considerations in Explainable AI Balancing Transparency and Complexity.html (7.5 KB)
24. Meta-Learning and AutoML
• 1. Meta-Learning Fundamentals Building Adaptive Models for Efficient Learning.html (14.2 KB)
• 2. Demystifying AutoML Streamlining Model Building with Automated Machine Learning.html (9.5 KB)
• 3. Optimizing Models Across Tasks Hyperparameter Tuning in Meta-Learning.html (10.5 KB)
• 4. Accelerating Model Performance with Transfer Learning in AutoML.html (11.5 KB)
• 5. Exploring Meta-Learning and AutoML Challenges, Opportunities, and Future Implic.html (18.0 KB)
25. Data Science Coding Challenges Mastering Concepts through Hands-On Exercises
• 1. Excel Mastery Unraveling Data Insights.html (0.2 KB)
• 2. Advanced Excel Data Analysis Mastering Techniques for In-Depth Insights & more+.html (0.2 KB)
• 3. Understanding Data Science Essentials (On practical Advanced level's).html (0.2 KB)
26. Multi-Language Data Access Bridging Python, R, and SQL (Only for Data Science)
• 1. Data Science Essentials Mastering Variables and Data Types.html (5.1 KB)
• 2. Mastering Data Science Advanced Operator and Expression Techniques.html (5.4 KB)
3. Advanced Data Visualization
• 1. Mastering Data Visualization Unlocking Insights through Effective Visual Commun.html (10.9 KB)
• 2. Mastering Data Visualization Choosing the Right Chart for Effective Communicati.html (12.7 KB)
• 3. Interactive Data Visualization with Python Creating Engaging Visualizations Usi.html (10.2 KB)
• 4. Mastering Geographic Data Visualization Unleash the Power of Spatial Insights.html (7.7 KB)
• 5. Data Visualization and Storytelling Crafting Compelling Narratives for Insights.html (10.2 KB)
4. Essential Machine Learning Algorithms
• 1. Mastering Machine Learning Algorithms A Comprehensive Guide for Data Science Pr.html (8.3 KB)
• 2. Supervised Learning Building Predictive Models for Data Analysis.html (11.9 KB)
• 3. Unsupervised Learning Exploring Patterns in Unlabeled Data.html (11.0 KB)
• 4. Ensemble Learning Boosting and Bagging for Improved Predictions.html (13.7 KB)
• 5. Mastering Classification and Regression in Machine Learning Advanced Techniques.html (12.2 KB)
5. Model Evaluation and Optimization
• 1. Evaluating Model Performance Metrics and Strategies for Machine Learning.html (7.5 KB)
• 2. Advanced Hyperparameter Tuning for Enhanced Model Performance in Data Science.html (6.3 KB)
• 3. Robust Model Evaluation with Cross-Validation Techniques in Data Science.html (10.8 KB)
• 4. Understanding the Bias-Variance Tradeoff in Data Science Achieving Optimal Mode.html (14.7 KB)
• 5. Advanced Model Optimization Fine-tuning Machine Learning Models for Optimal Per.html (13.8 KB)
6. Advanced Feature Engineering
• 1. Advanced Feature Importance Techniques for Machine Learning Models.html (12.9 KB)
• 2. Advanced Dimensionality Reduction Techniques in Data Science.html (11.9 KB)
• 3. Handling Categorical Data in Machine Learning Strategies and Techniques for Dat.html (9.7 KB)
• 4. Advanced Feature Scaling Techniques for Unbiased Machine Learning.html (9.9 KB)
• 5. Time Series Feature Engineering Enhancing Machine Learning Models with Temporal.html (11.3 KB)
7. Exploring Deep Learning
• 1. Deep Learning Fundamentals Exploring Concepts and Architectures.html (8.3 KB)
• 2. Deep Dive into Neural Networks Building Blocks of Deep Learning Models.html (9.4 KB)
• 3. Advanced Image Processing and Recognition Using Convolutional Neural Networks (C.html (8.8 KB)
• 4. Advanced Recurrent Neural Networks (RNNs) for Sequential Data Modeling.html (6.7 KB)
• 5. Efficient Deep Learning with Transfer Learning Unlocking the Power of Pre-Train.html (12.0 KB)
8. Natural Language Processing (NLP)
• 1. Advanced Natural Language Processing Foundations and Concepts for Data Science.html (15.8 KB)
• 2. Text Preprocessing in NLP Clean and Transform Text Data Effectively.html (12.5 KB)
• 3. Advanced Named Entity Recognition (NER) for Text Analysis.html (8.1 KB)
• 4. Sentiment Analysis Extracting Emotions from Textual Data.html (9.7 KB)
• 5. Advanced Named Entity Recognition (NER) for Text Analysis.html (10.2 KB)
9. Recommendation Systems
• 1. Mastering Recommendation Systems Personalized Content Delivery.html (15.9 KB)
• 2. Advanced Collaborative Filtering Techniques for Recommendation Systems.html (20.4 KB)
• 3. Advanced Content-Based Filtering for Personalized Recommendations in Data Scienc.html (12.2 KB)
• 4. Advanced Matrix Factorization Models for Recommendation Systems.html (11.8 KB)
• 5. Evaluating Recommendation Systems Metrics for Performance Assessment.html (6.4 KB)
• Bonus Resources.txt (0.4 KB)