CBTNuggets - CompTIA DataX (DY0-001) Online Training (7.2025)

Creation Time	Nov. 4, 2025, 7:32 p.m.
Last Access Time	Nov. 4, 2025, 7:38 p.m.
File Size	6.0 GB
Keywords	CBTNuggets Training CompTIA - 7 2025 DataX DY0-001 Online
Total Requests	2
Total Files	350
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39. Use Models to Understand IP Networking/9. Solution.mp4 224.0 MB
39. Use Models to Understand IP Networking/8. Validation.mp4 163.7 MB
39. Use Models to Understand IP Networking/5. Layer 3, Network Layer.mp4 114.5 MB
39. Use Models to Understand IP Networking/6. Layer 2, Data Link Layer.mp4 91.9 MB
39. Use Models to Understand IP Networking/4. Application and Transport Layers.mp4 91.3 MB
2. Assess your Data Science Knowledge Gaps for DataX/2. Review Questions with Answers Explained.mp4 71.2 MB
27. Compare PyTorch and TensorFlow for Deep Learning/3. TensorFlow Multiclass Classifier.mp4 53.4 MB
27. Compare PyTorch and TensorFlow for Deep Learning/4. PyTorch Multiclass Classifier.mp4 52.2 MB
14. Explore Data Transformation for Data Science/9. Challenge 🎉.mp4 52.0 MB
39. Use Models to Understand IP Networking/3. Network Models.mp4 51.8 MB
24. Analyze Core Artificial Neural Network Concepts/6. Different Activation Functions.mp4 44.6 MB
39. Use Models to Understand IP Networking/7. Layer 1, Physical Layer.mp4 44.1 MB
1. Explore Data Science and Resources for DataX/2. Introduction Part 2.mp4 43.6 MB
37. Apply Feature Extraction for Image Perception/2. Image Preprocessing Deep Dive.mp4 42.5 MB
8. Perform Statistical Testing for Data Science/3. Confidence Intervals and Z-Scores.mp4 42.2 MB
39. Use Models to Understand IP Networking/2. IP Networking Overview.mp4 41.2 MB
28. Explore Natural Language Processing (NLP) Concepts/5. Text Analysis Semantic Matching.mp4 39.6 MB
36. Apply Computer Vision for Image Understanding/2. Image Preprocessing.mp4 38.9 MB
29. Explore Tokenization, Gen AI, and LLMs in NLP/5. What are Large Language Models (LLMs).mp4 38.8 MB
26. Apply Neural Network Concepts to Deep Learning/Attention Is All You Need.wav 38.2 MB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/5. Bag of Words, TF-IDF, and TensorFlow Embedding Projector.mp4 37.9 MB
8. Perform Statistical Testing for Data Science/4. Hypothesis Testing.mp4 36.0 MB
19. Build a Supervised Learning Regression Model/3. What is Linear Regression.mp4 35.0 MB
12. Explore Data Analysis & Variables for Data Science/7. Real-world Scenarios.mp4 34.9 MB
19. Build a Supervised Learning Regression Model/4. Predicting Disease with Linear Regression.mp4 34.8 MB
26. Apply Neural Network Concepts to Deep Learning/2. Gradient Problems.mp4 34.0 MB
13. Explore Multivariate Analysis and Quality in DS/3. Multivariate Analysis.mp4 33.9 MB
23. Explore Decision Trees and Ensemble Methods/2. What is a Decision Tree.mp4 33.4 MB
7. Apply Probability & Statistics for Data Science/3. Discrete, Continuous, and Cumulative Distributions.mp4 33.3 MB
25. Explore ANN Training Techniques & Gradient Descent/4. Training a Neural Network Formula (continued).mp4 33.1 MB
29. Explore Tokenization, Gen AI, and LLMs in NLP/3. Sentence and Subword Tokenization.mp4 32.9 MB
17. Validate Models and Communicate Data Effectively/8. Communicating Results to Stakeholders.mp4 32.9 MB
8. Perform Statistical Testing for Data Science/2. Inferential Statistics.mp4 32.3 MB
1. Explore Data Science and Resources for DataX/6. Machine Learning & Data Science Application Examples.mp4 32.1 MB
23. Explore Decision Trees and Ensemble Methods/7. A Practical Decision Tree Iris Dataset.mp4 31.9 MB
3. Explore Data Science Tools and Lifecycles/3. CRISP-DM (Cross-Industry Standard Process for Data Mining).mp4 31.8 MB
37. Apply Feature Extraction for Image Perception/4. Contrast, Normalization, Color Space Conversion & Hole Filling.mp4 31.7 MB
36. Apply Computer Vision for Image Understanding/5. Image Extraction.mp4 31.4 MB
27. Compare PyTorch and TensorFlow for Deep Learning/2. Compare PyTorch Vs. TensorFlow.mp4 31.4 MB
13. Explore Multivariate Analysis and Quality in DS/2. Univariate & Bivariate Analysis Review (Spaced Retrieval).mp4 31.0 MB
22. Classify Data with the Naive Bayes Algorithm/4. Naive Bayes On the Iris Dataset.mp4 31.0 MB
9. Apply Linear Algebra to Data Science Problems/5. Matrix Operations.mp4 30.8 MB
9. Apply Linear Algebra to Data Science Problems/4. Dot Product & Vector Distance Metrics.mp4 30.2 MB
34. Compare Linear and Nonlinear Programming Methods/4. Visualize the Feasibility Region.mp4 30.2 MB
15. Augment and Feature Engineer Data for Data Science/8. Cleaning Data.mp4 30.0 MB
23. Explore Decision Trees and Ensemble Methods/3. Visualizing Decision Trees.mp4 29.7 MB
6. Explore Change Using Calculus for Data Science/3. Chain Rule For Nested Functions.mp4 29.0 MB
20. Build a Supervised Learning Classification Model/4. Implement Logistic Regression Model.mp4 28.8 MB
31. Use Advanced Text Preparation for Machine Learning/2. POS Tagging.mp4 28.7 MB
4. Examine Data Science Code Syntax and Workflows/4. Basic Python Syntax.mp4 28.7 MB
26. Apply Neural Network Concepts to Deep Learning/6. The Transformer Architecture.mp4 28.6 MB
25. Explore ANN Training Techniques & Gradient Descent/3. Training a Neural Network Loss Functions (continued).mp4 28.5 MB
31. Use Advanced Text Preparation for Machine Learning/8. Solution.mp4 28.5 MB
25. Explore ANN Training Techniques & Gradient Descent/2. Training Neural Networks.mp4 28.3 MB
30. Prepare Text for Natural Language Processing/5. Removing Stop Words.mp4 28.2 MB
28. Explore Natural Language Processing (NLP) Concepts/4. Text Analysis Matching Models.mp4 27.9 MB
36. Apply Computer Vision for Image Understanding/3. Object Detection with Pretrained Models.mp4 27.8 MB
4. Examine Data Science Code Syntax and Workflows/2. Python Libraries & Dependency Licenses for Data Science.mp4 27.7 MB
30. Prepare Text for Natural Language Processing/2. Text Preparation and Representation.mp4 27.6 MB
26. Apply Neural Network Concepts to Deep Learning/3. Optimizers in Deep Learning.mp4 27.3 MB
33. Explore Foundations of Optimization/3. Optimization in Machine Learning.mp4 27.2 MB
18. Analyze Model Deployment and MLOps/6. Hybrid & Edge Deployment.mp4 27.1 MB
29. Explore Tokenization, Gen AI, and LLMs in NLP/4. What is Language Generation.mp4 27.1 MB
33. Explore Foundations of Optimization/5. Feasibility Regions.mp4 27.1 MB
37. Apply Feature Extraction for Image Perception/5. Feature Extraction Deep Dive.mp4 26.7 MB
20. Build a Supervised Learning Classification Model/5. Logistic Regression Breakdown.mp4 26.5 MB
28. Explore Natural Language Processing (NLP) Concepts/3. What is Text Analysis (aka Text Mining & Text Analytics).mp4 25.8 MB
29. Explore Tokenization, Gen AI, and LLMs in NLP/2. What is Tokenization (preprocessing).mp4 25.8 MB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/4. Python One-Hot Encoding Code Example.mp4 25.8 MB
1. Explore Data Science and Resources for DataX/5. Data Science Lifecycle & Machine Learning Approaches.mp4 25.8 MB
37. Apply Feature Extraction for Image Perception/3. More Geometric Transformations.mp4 25.8 MB
15. Augment and Feature Engineer Data for Data Science/7. Left, Right, Full, Anti, and Fuzzy Joins (continued SQL JOINS).mp4 25.8 MB
35. Explore Specialized Machine Learning Optimization/6. Bandit Problems.mp4 25.6 MB
26. Apply Neural Network Concepts to Deep Learning/4. What is Deep Learning.mp4 25.1 MB
16. Explore Statistical and Machine Learning Models/8. Loss Functions and Model Evaluations.mp4 25.0 MB
31. Use Advanced Text Preparation for Machine Learning/3. Regular Expressions (Regex).mp4 25.0 MB
18. Analyze Model Deployment and MLOps/8. MLOps Lifecycle & Concepts.mp4 24.9 MB
16. Explore Statistical and Machine Learning Models/2. Regression Models.mp4 24.5 MB
17. Validate Models and Communicate Data Effectively/5. Data Drift Vs Concepts Drift.mp4 24.5 MB
23. Explore Decision Trees and Ensemble Methods/5. Impurity Measures Gini and Entropy.mp4 24.3 MB
16. Explore Statistical and Machine Learning Models/7. Causal Inference & Bias-Variance Trade-Off.mp4 24.3 MB
25. Explore ANN Training Techniques & Gradient Descent/5. Training Techniques Regularization.mp4 24.1 MB
1. Explore Data Science and Resources for DataX/3. The Origin of Data Science.mp4 24.1 MB
1. Explore Data Science and Resources for DataX/1. Introduction.mp4 24.0 MB
24. Analyze Core Artificial Neural Network Concepts/5. ANN Components.mp4 24.0 MB
5. Review Best Practices, Composition, & Requirements/5. Software Composition Analysis Part 2.mp4 23.9 MB
34. Compare Linear and Nonlinear Programming Methods/5. Integer Programming.mp4 23.4 MB
22. Classify Data with the Naive Bayes Algorithm/6. Naive Bayes Zero Frequency Problem.mp4 23.3 MB
24. Analyze Core Artificial Neural Network Concepts/1. Introduction.mp4 23.3 MB
22. Classify Data with the Naive Bayes Algorithm/2. Bayes' Theorem.mp4 23.2 MB
33. Explore Foundations of Optimization/6. Constrained and Unconstrained Optimization.mp4 22.9 MB
21. Explore Quadratic and Linear Discriminant Analysis/2. Linear and Logistic Regression Vs. Discriminant Analysis (DA).mp4 22.8 MB
17. Validate Models and Communicate Data Effectively/2. What is Model Validation.mp4 22.4 MB
17. Validate Models and Communicate Data Effectively/1. Introduction.mp4 22.4 MB
34. Compare Linear and Nonlinear Programming Methods/2. Linear Programming Concepts.mp4 22.3 MB
24. Analyze Core Artificial Neural Network Concepts/3. What is a Perceptron.mp4 22.0 MB
22. Classify Data with the Naive Bayes Algorithm/5. Naive Bayes On the Titanic Dataset.mp4 21.8 MB
6. Explore Change Using Calculus for Data Science/4. Partial Derivatives Multivariable Functions.mp4 21.8 MB
20. Build a Supervised Learning Classification Model/2. Linear Regression Vs Logistic Regression.mp4 21.6 MB
8. Perform Statistical Testing for Data Science/5. One-Sample, Two-Sample, and Paired t-Tests.mp4 21.3 MB
26. Apply Neural Network Concepts to Deep Learning/7. GANs, Diffusion, and Special Learning Techniques.mp4 21.3 MB
11. Explore Data Ingestion & Storage for Data Science/3. Ingestion Infrastructure.mp4 21.2 MB
14. Explore Data Transformation for Data Science/7. Structural Transformations.mp4 21.1 MB
20. Build a Supervised Learning Classification Model/3. Implement Linear Regression Model.mp4 21.0 MB
26. Apply Neural Network Concepts to Deep Learning/1. Introduction.mp4 21.0 MB
15. Augment and Feature Engineer Data for Data Science/6. Merging and Combining Data with SQL JOINS.mp4 21.0 MB
19. Build a Supervised Learning Regression Model/6. Predicting Disease Evaluation.mp4 20.8 MB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/1. Introduction.mp4 20.8 MB
35. Explore Specialized Machine Learning Optimization/2. What is the Goal of ML Optimization.mp4 20.6 MB
24. Analyze Core Artificial Neural Network Concepts/2. What is an Artificial Neural Network.mp4 20.6 MB
7. Apply Probability & Statistics for Data Science/2. Probability Distributions.mp4 20.4 MB
35. Explore Specialized Machine Learning Optimization/7. WalkthroughSolution Video.mp4 20.4 MB
13. Explore Multivariate Analysis and Quality in DS/4. Data Quality.mp4 20.3 MB
5. Review Best Practices, Composition, & Requirements/9. Solution Video (optional).mp4 20.2 MB
17. Validate Models and Communicate Data Effectively/4. Design Constraints.mp4 20.2 MB
24. Analyze Core Artificial Neural Network Concepts/8. Challenge Build an ANN 🎉.mp4 20.2 MB
34. Compare Linear and Nonlinear Programming Methods/6. Linear Vs Nonlinear Programming.mp4 20.1 MB
18. Analyze Model Deployment and MLOps/7. Cluster & Cloud Deployment.mp4 19.8 MB
9. Apply Linear Algebra to Data Science Problems/3. Vector Operations.mp4 19.5 MB
23. Explore Decision Trees and Ensemble Methods/1. Introduction.mp4 19.5 MB
35. Explore Specialized Machine Learning Optimization/5. Constrained Vs Unconstrained Optimization.mp4 19.4 MB
10. Examine Key Data Sources for Data Science/6. Synthetic Data.mp4 19.0 MB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/9. GloVe Global Vectors for Word Representation.mp4 18.9 MB
20. Build a Supervised Learning Classification Model/7. Solution Video.mp4 18.8 MB
21. Explore Quadratic and Linear Discriminant Analysis/3. What is Discriminant Analysis (DA).mp4 18.7 MB
8. Perform Statistical Testing for Data Science/6. ANOVA, Chi-Squared Tests, and Correlation.mp4 18.7 MB
19. Build a Supervised Learning Regression Model/5. Predicting Disease EDA.mp4 18.6 MB
35. Explore Specialized Machine Learning Optimization/3. Visualize Gradient Descent in 1D.mp4 18.6 MB
23. Explore Decision Trees and Ensemble Methods/6. Growing the Tree Step by Step with Cryptocurrency.mp4 18.5 MB
21. Explore Quadratic and Linear Discriminant Analysis/4. What is Linear Discriminant Analysis (LDA).mp4 18.5 MB
6. Explore Change Using Calculus for Data Science/2. Derivatives Measuring Change.mp4 18.5 MB
36. Apply Computer Vision for Image Understanding/4. OCR and Segmentation.mp4 18.2 MB
28. Explore Natural Language Processing (NLP) Concepts/2. What is NLP.mp4 18.2 MB
15. Augment and Feature Engineer Data for Data Science/4. Ground Truth Labeling.mp4 18.1 MB
25. Explore ANN Training Techniques & Gradient Descent/1. Introduction.mp4 18.1 MB
12. Explore Data Analysis & Variables for Data Science/1. Introduction.mp4 18.1 MB
4. Examine Data Science Code Syntax and Workflows/7. Solution Video.mp4 18.0 MB
9. Apply Linear Algebra to Data Science Problems/6. Inverse & Solving Linear Systems.mp4 17.8 MB
11. Explore Data Ingestion & Storage for Data Science/7. Flat Files, Semi-Structured, Unstructured, and Compression.mp4 17.8 MB
5. Review Best Practices, Composition, & Requirements/2. DAMA and the DMBOK.mp4 17.6 MB
15. Augment and Feature Engineer Data for Data Science/10. Outlier Detection.mp4 17.5 MB
30. Prepare Text for Natural Language Processing/6. CHALLENGE 🎉.mp4 17.5 MB
3. Explore Data Science Tools and Lifecycles/5. SEMMA (Sample, Explore, Modify, Model, Assess).mp4 17.3 MB
15. Augment and Feature Engineer Data for Data Science/2. Explore the Datasets.mp4 17.2 MB
11. Explore Data Ingestion & Storage for Data Science/4. Data Ingestion Pipeline.mp4 17.2 MB
18. Analyze Model Deployment and MLOps/5. On-Premises Deployment.mp4 17.0 MB
30. Prepare Text for Natural Language Processing/4. Stemming and Lemmatization.mp4 17.0 MB
33. Explore Foundations of Optimization/2. What is Optimization.mp4 16.9 MB
16. Explore Statistical and Machine Learning Models/4. Modeling Time Series.mp4 16.8 MB
35. Explore Specialized Machine Learning Optimization/4. Different Flavors of Gradient Descent.mp4 16.7 MB
31. Use Advanced Text Preparation for Machine Learning/5. Data Augmentation.mp4 16.6 MB
10. Examine Key Data Sources for Data Science/7. Public Data.mp4 16.6 MB
4. Examine Data Science Code Syntax and Workflows/5. Basic R Syntax.mp4 16.5 MB
12. Explore Data Analysis & Variables for Data Science/5. Univariate Analysis.mp4 16.5 MB
18. Analyze Model Deployment and MLOps/9. MLOps Automation & Versioning.mp4 16.4 MB
30. Prepare Text for Natural Language Processing/3. Tokenization with N-grams.mp4 16.3 MB
19. Build a Supervised Learning Regression Model/2. What is Supervised Learning.mp4 16.2 MB
7. Apply Probability & Statistics for Data Science/5. Central Limit Theorem, Monte Carlo Simulations.mp4 16.0 MB
16. Explore Statistical and Machine Learning Models/5. Survival Analysis.mp4 16.0 MB
12. Explore Data Analysis & Variables for Data Science/3. Types of Analysis Variables.mp4 16.0 MB
21. Explore Quadratic and Linear Discriminant Analysis/7. Checking Normality for LDA Shapiro-Wilk Test.mp4 15.9 MB
9. Apply Linear Algebra to Data Science Problems/2. Scalars, Vectors, Matrices, and Tensors.mp4 15.9 MB
15. Augment and Feature Engineer Data for Data Science/3. Data Augmentation and Enrichment.mp4 15.9 MB
18. Analyze Model Deployment and MLOps/4. Virtualization.mp4 15.9 MB
10. Examine Key Data Sources for Data Science/2. Generated Data.mp4 15.8 MB
30. Prepare Text for Natural Language Processing/7. Solution.mp4 15.8 MB
22. Classify Data with the Naive Bayes Algorithm/3. Naive Bayes The Naive Part.mp4 15.7 MB
30. Prepare Text for Natural Language Processing/1. Introduction.mp4 15.6 MB
33. Explore Foundations of Optimization/7. Gradient Descent Vs Stochastic Gradient Descent.mp4 15.5 MB
8. Perform Statistical Testing for Data Science/1. Introduction.mp4 15.5 MB
18. Analyze Model Deployment and MLOps/10. MLOps Testing & Versioning.mp4 15.3 MB
20. Build a Supervised Learning Classification Model/6. CHALLENGE 🎉.mp4 15.2 MB
36. Apply Computer Vision for Image Understanding/1. Introduction.mp4 15.1 MB
21. Explore Quadratic and Linear Discriminant Analysis/6. What is Quadratic Discriminant Analysis (QDA).mp4 15.1 MB
7. Apply Probability & Statistics for Data Science/4. Types of Continuous Distributions.mp4 15.0 MB
37. Apply Feature Extraction for Image Perception/6. Challenge 🎉.mp4 14.9 MB
25. Explore ANN Training Techniques & Gradient Descent/7. Solution.mp4 14.8 MB
34. Compare Linear and Nonlinear Programming Methods/3. Linear Programming with Python.mp4 14.7 MB
22. Classify Data with the Naive Bayes Algorithm/1. Introduction.mp4 14.7 MB
1. Explore Data Science and Resources for DataX/4. What is Data Science.mp4 14.6 MB
16. Explore Statistical and Machine Learning Models/1. Introduction.mp4 14.4 MB
16. Explore Statistical and Machine Learning Models/3. Classification Models.mp4 14.3 MB
39. Use Models to Understand IP Networking/1. Intro.mp4 14.3 MB
4. Examine Data Science Code Syntax and Workflows/3. Data Science Directory Structures.mp4 14.2 MB
33. Explore Foundations of Optimization/4. Decision Variables, Objective Functions, and Constraints.mp4 14.1 MB
6. Explore Change Using Calculus for Data Science/5. Integration Accumulating Totals.mp4 14.1 MB
28. Explore Natural Language Processing (NLP) Concepts/1. Introduction.mp4 14.1 MB
7. Apply Probability & Statistics for Data Science/6. Solution.mp4 13.7 MB
16. Explore Statistical and Machine Learning Models/6. Longitudinal Studies.mp4 13.7 MB
3. Explore Data Science Tools and Lifecycles/10. Optional Solution Walkthrough.mp4 13.6 MB
36. Apply Computer Vision for Image Understanding/6. Sensor Fusion.mp4 13.5 MB
4. Examine Data Science Code Syntax and Workflows/6. CHALLENGE Clean & Process Sales Data.mp4 13.4 MB
18. Analyze Model Deployment and MLOps/1. Introduction.mp4 13.3 MB
15. Augment and Feature Engineer Data for Data Science/5. Feature Engineering.mp4 13.1 MB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/3. One-Hot Encoding.mp4 13.1 MB
29. Explore Tokenization, Gen AI, and LLMs in NLP/1. Introduction.mp4 13.0 MB
26. Apply Neural Network Concepts to Deep Learning/5. Recurrent Neural Networks (RNNs), LSTMS, and GRUs.mp4 12.9 MB
14. Explore Data Transformation for Data Science/8. Feature Extraction.mp4 12.7 MB
23. Explore Decision Trees and Ensemble Methods/10. Challenge 🎉.mp4 12.4 MB
31. Use Advanced Text Preparation for Machine Learning/6. Text Representations.mp4 12.3 MB
13. Explore Multivariate Analysis and Quality in DS/7. Solution.mp4 12.3 MB
14. Explore Data Transformation for Data Science/6. Transformation Functions.mp4 12.2 MB
5. Review Best Practices, Composition, & Requirements/4. Software Composition Analysis.mp4 12.1 MB
12. Explore Data Analysis & Variables for Data Science/6. Bivariate Analysis.mp4 12.1 MB
19. Build a Supervised Learning Regression Model/1. Introduction.mp4 12.0 MB
2. Assess your Data Science Knowledge Gaps for DataX/1. Introduction.mp4 12.0 MB
4. Examine Data Science Code Syntax and Workflows/1. Introduction.mp4 12.0 MB
5. Review Best Practices, Composition, & Requirements/3. Requirement Gathering.mp4 12.0 MB
17. Validate Models and Communicate Data Effectively/3. Performance Metrics.mp4 11.9 MB
6. Explore Change Using Calculus for Data Science/7. Solution Video.mp4 11.9 MB
19. Build a Supervised Learning Regression Model/7. Linear regression Vs Logistic regression.mp4 11.9 MB
24. Analyze Core Artificial Neural Network Concepts/7. Training Neural Networks.mp4 11.7 MB
34. Compare Linear and Nonlinear Programming Methods/7. Visualize the Feasibility Region.mp4 11.7 MB
3. Explore Data Science Tools and Lifecycles/2. Implementing Best Practices in the Data Science Lifecycle.mp4 11.7 MB
36. Apply Computer Vision for Image Understanding/7. Solution.mp4 11.6 MB
18. Analyze Model Deployment and MLOps/Skill_14 DataX CompTIA Notes.svg 11.6 MB
37. Apply Feature Extraction for Image Perception/1. Introduction.mp4 11.5 MB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/2. To Vectorize or Not to Vectorize.mp4 11.5 MB
12. Explore Data Analysis & Variables for Data Science/8. Challenge.mp4 11.5 MB
20. Build a Supervised Learning Classification Model/1. Introduction.mp4 11.3 MB
14. Explore Data Transformation for Data Science/4. Scaling and Normalization.mp4 11.2 MB
3. Explore Data Science Tools and Lifecycles/4. TDSP (Team Data Science Process).mp4 11.2 MB
10. Examine Key Data Sources for Data Science/4. Sensor Data.mp4 11.1 MB
27. Compare PyTorch and TensorFlow for Deep Learning/1. Introduction.mp4 11.1 MB
5. Review Best Practices, Composition, & Requirements/7. API Integration.mp4 11.0 MB
6. Explore Change Using Calculus for Data Science/6. CHALLENGE 🎉.mp4 11.0 MB
23. Explore Decision Trees and Ensemble Methods/9. What Are Ensemble Methods.mp4 10.9 MB
15. Augment and Feature Engineer Data for Data Science/1. Introduction.mp4 10.9 MB
31. Use Advanced Text Preparation for Machine Learning/4. Spelling Normalization.mp4 10.9 MB
17. Validate Models and Communicate Data Effectively/7. Benchmarking.mp4 10.7 MB
11. Explore Data Ingestion & Storage for Data Science/1. Introduction.mp4 10.7 MB
23. Explore Decision Trees and Ensemble Methods/8. What is a Random Forest.mp4 10.6 MB
23. Explore Decision Trees and Ensemble Methods/4. How Do Decision Trees Grow.mp4 10.6 MB
14. Explore Data Transformation for Data Science/2. Encoding Categorical Data.mp4 10.5 MB
10. Examine Key Data Sources for Data Science/3. Records.mp4 10.4 MB
18. Analyze Model Deployment and MLOps/2. Containerization.mp4 10.3 MB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/8. Word2Vec Coding Example.mp4 10.2 MB
10. Examine Key Data Sources for Data Science/5. Transactions & Experiments.mp4 10.1 MB
35. Explore Specialized Machine Learning Optimization/1. Introduction.mp4 9.9 MB
24. Analyze Core Artificial Neural Network Concepts/4. Activation Function Breakdown.mp4 9.9 MB
21. Explore Quadratic and Linear Discriminant Analysis/5. LCA Vs. PCA.mp4 9.8 MB
33. Explore Foundations of Optimization/1. Introduction.mp4 9.8 MB
5. Review Best Practices, Composition, & Requirements/6. Documentation and Code Quality.mp4 9.7 MB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/7. Word Embeddings with Word2Vec.mp4 9.5 MB
25. Explore ANN Training Techniques & Gradient Descent/6. Challenge.mp4 9.1 MB
34. Compare Linear and Nonlinear Programming Methods/1. Introduction.mp4 9.1 MB
25. Explore ANN Training Techniques & Gradient Descent/skill_21_DataX.svg 9.0 MB
7. Apply Probability & Statistics for Data Science/1. Introduction.mp4 8.8 MB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/6. TF-IDF Coding Example.mp4 8.5 MB
18. Analyze Model Deployment and MLOps/3. Container Orchestration.mp4 8.4 MB
11. Explore Data Ingestion & Storage for Data Science/6. Structured Storage.mp4 8.1 MB
13. Explore Multivariate Analysis and Quality in DS/1. Introduction.mp4 7.9 MB
38. Identify Knowledge Gaps with the DataX SkillScan/34. Question 34.mp4 7.7 MB
11. Explore Data Ingestion & Storage for Data Science/2. Data Ingestion.mp4 7.6 MB
14. Explore Data Transformation for Data Science/3. Label Encoding.mp4 7.5 MB
28. Explore Natural Language Processing (NLP) Concepts/skill_24_notes.svg 7.5 MB
9. Apply Linear Algebra to Data Science Problems/1. Introductions.mp4 7.4 MB
38. Identify Knowledge Gaps with the DataX SkillScan/4. Question 4.mp4 7.3 MB
13. Explore Multivariate Analysis and Quality in DS/5. Nonlinearity.mp4 7.3 MB
3. Explore Data Science Tools and Lifecycles/1. Introduction.mp4 6.9 MB
31. Use Advanced Text Preparation for Machine Learning/1. Introduction.mp4 6.9 MB
6. Explore Change Using Calculus for Data Science/1. Python Introduction.mp4 6.5 MB
14. Explore Data Transformation for Data Science/5. Standardization.mp4 6.5 MB
12. Explore Data Analysis & Variables for Data Science/2. Exploratory Data Analysis Basics.mp4 6.5 MB
15. Augment and Feature Engineer Data for Data Science/9. Interpolation and Extrapolation.mp4 6.4 MB
22. Classify Data with the Naive Bayes Algorithm/skill_18_DataX.excalidraw.svg 6.3 MB
29. Explore Tokenization, Gen AI, and LLMs in NLP/7. Challenge Solution.mp4 6.3 MB
17. Validate Models and Communicate Data Effectively/6. Aligning Business Requirements.mp4 6.2 MB
21. Explore Quadratic and Linear Discriminant Analysis/1. Introduction.mp4 6.1 MB
7. Apply Probability & Statistics for Data Science/skill_35.excalidraw.svg 6.0 MB
22. Classify Data with the Naive Bayes Algorithm/7. Handling Continuous, High-Dimensional, and Missing Data.mp4 5.8 MB
14. Explore Data Transformation for Data Science/1. Introduction.mp4 5.7 MB
10. Examine Key Data Sources for Data Science/1. Introduction.mp4 5.6 MB
8. Perform Statistical Testing for Data Science/7. Challenge 🎉.mp4 5.5 MB
3. Explore Data Science Tools and Lifecycles/7. CRISP-DM Scenario.mp4 5.5 MB
33. Explore Foundations of Optimization/skill_29.excalidraw.svg 5.5 MB
35. Explore Specialized Machine Learning Optimization/skill_31.excalidraw.svg 5.4 MB
31. Use Advanced Text Preparation for Machine Learning/skill_27.excalidraw.svg 5.3 MB
17. Validate Models and Communicate Data Effectively/9. CHALLENGE 🎉.mp4 5.3 MB
5. Review Best Practices, Composition, & Requirements/1. Introduction.mp4 5.1 MB
38. Identify Knowledge Gaps with the DataX SkillScan/5. Question 5.mp4 5.0 MB
38. Identify Knowledge Gaps with the DataX SkillScan/6. Question 6.mp4 4.9 MB
12. Explore Data Analysis & Variables for Data Science/4. Analyzing Health Survey Data.mp4 4.6 MB
13. Explore Multivariate Analysis and Quality in DS/6. Challenge.mp4 4.5 MB
22. Classify Data with the Naive Bayes Algorithm/skill_18_DataX.excalidraw.png 4.5 MB
11. Explore Data Ingestion & Storage for Data Science/5. Orchestration Vs Automation.mp4 4.4 MB
38. Identify Knowledge Gaps with the DataX SkillScan/9. Question 9.mp4 4.4 MB
38. Identify Knowledge Gaps with the DataX SkillScan/11. Question 11.mp4 4.3 MB
29. Explore Tokenization, Gen AI, and LLMs in NLP/6. Challenge 🎉.mp4 4.1 MB
38. Identify Knowledge Gaps with the DataX SkillScan/17. Question 17.mp4 4.1 MB
31. Use Advanced Text Preparation for Machine Learning/7. Challenge 🎉.mp4 3.9 MB
38. Identify Knowledge Gaps with the DataX SkillScan/3. Question 3.mp4 3.9 MB
11. Explore Data Ingestion & Storage for Data Science/8. CHALLENGE 🎉.mp4 3.6 MB
3. Explore Data Science Tools and Lifecycles/6. CHALLENGE.mp4 3.5 MB
38. Identify Knowledge Gaps with the DataX SkillScan/35. Question 35.mp4 3.5 MB
24. Analyze Core Artificial Neural Network Concepts/9. Solution.mp4 3.4 MB
38. Identify Knowledge Gaps with the DataX SkillScan/30. Question 30.mp4 3.4 MB
38. Identify Knowledge Gaps with the DataX SkillScan/1. Question 1.mp4 3.4 MB
38. Identify Knowledge Gaps with the DataX SkillScan/14. Question 14.mp4 3.3 MB
38. Identify Knowledge Gaps with the DataX SkillScan/28. Question 28.mp4 3.3 MB
6. Explore Change Using Calculus for Data Science/skill_34.excalidraw.svg 3.1 MB
38. Identify Knowledge Gaps with the DataX SkillScan/13. Question 13.mp4 3.0 MB
38. Identify Knowledge Gaps with the DataX SkillScan/15. Question 15.mp4 3.0 MB
3. Explore Data Science Tools and Lifecycles/9. SEMMA Scenario.mp4 2.9 MB
38. Identify Knowledge Gaps with the DataX SkillScan/33. Question 33.mp4 2.9 MB
38. Identify Knowledge Gaps with the DataX SkillScan/29. Question 29.mp4 2.9 MB
38. Identify Knowledge Gaps with the DataX SkillScan/2. Question 2.mp4 2.9 MB
38. Identify Knowledge Gaps with the DataX SkillScan/10. Question 10.mp4 2.8 MB
38. Identify Knowledge Gaps with the DataX SkillScan/16. Question 16.mp4 2.8 MB
38. Identify Knowledge Gaps with the DataX SkillScan/19. Question 19.mp4 2.8 MB
38. Identify Knowledge Gaps with the DataX SkillScan/27. Question 27.mp4 2.7 MB
38. Identify Knowledge Gaps with the DataX SkillScan/18. Question 18.mp4 2.7 MB
23. Explore Decision Trees and Ensemble Methods/skill_19_DataX.excalidraw.svg 2.6 MB
38. Identify Knowledge Gaps with the DataX SkillScan/23. Question 23.mp4 2.6 MB
38. Identify Knowledge Gaps with the DataX SkillScan/36. Question 36.mp4 2.5 MB
38. Identify Knowledge Gaps with the DataX SkillScan/8. Question 8.mp4 2.5 MB
38. Identify Knowledge Gaps with the DataX SkillScan/22. Question 22.mp4 2.4 MB
29. Explore Tokenization, Gen AI, and LLMs in NLP/skill_25.svg 2.4 MB
3. Explore Data Science Tools and Lifecycles/8. TDSP Scenario.mp4 2.3 MB
38. Identify Knowledge Gaps with the DataX SkillScan/20. Question 20.mp4 2.3 MB
9. Apply Linear Algebra to Data Science Problems/7. CHALLENGE 🎉.mp4 2.3 MB
38. Identify Knowledge Gaps with the DataX SkillScan/21. Question 21.mp4 2.2 MB
38. Identify Knowledge Gaps with the DataX SkillScan/32. Question 32.mp4 2.2 MB
30. Prepare Text for Natural Language Processing/skill_26.excalidraw.svg 2.2 MB
16. Explore Statistical and Machine Learning Models/9. Challenge 🎉.mp4 2.2 MB
38. Identify Knowledge Gaps with the DataX SkillScan/7. Question 7.mp4 2.2 MB
36. Apply Computer Vision for Image Understanding/pic.png 2.1 MB
37. Apply Feature Extraction for Image Perception/pic.png 2.1 MB
38. Identify Knowledge Gaps with the DataX SkillScan/26. Question 26.mp4 2.0 MB
38. Identify Knowledge Gaps with the DataX SkillScan/31. Question 31.mp4 2.0 MB
38. Identify Knowledge Gaps with the DataX SkillScan/24. Question 24.mp4 1.9 MB
8. Perform Statistical Testing for Data Science/skill_36.excalidraw.svg 1.9 MB
38. Identify Knowledge Gaps with the DataX SkillScan/25. Question 25.mp4 1.8 MB
9. Apply Linear Algebra to Data Science Problems/skill_37.excalidraw.svg 1.6 MB
34. Compare Linear and Nonlinear Programming Methods/skill_30.excalidraw.svg 1.6 MB
38. Identify Knowledge Gaps with the DataX SkillScan/12. Question 12.mp4 1.6 MB
36. Apply Computer Vision for Image Understanding/skill_32.excalidraw.svg 1.1 MB
19. Build a Supervised Learning Regression Model/Skill_15_DataX_CompTIA.svg 1.1 MB
26. Apply Neural Network Concepts to Deep Learning/skill_22.excalidraw.svg 1.1 MB
24. Analyze Core Artificial Neural Network Concepts/skill_20_DataX.excalidraw.svg 1002.4 KB
37. Apply Feature Extraction for Image Perception/skill_33.excalidraw.svg 932.8 KB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/skill_notes.png 899.8 KB
5. Review Best Practices, Composition, & Requirements/8. Challenge 🎉.mp4 777.1 KB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/vectors.tsv 471.5 KB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/word2vec_vectors.tsv 231.7 KB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/time_spent_hypothesis_test.csv 54.3 KB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/glove_vectors.tsv 12.4 KB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/metadata.tsv 1.4 KB
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/word2vec_metadata.tsv 948 bytes
32. Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe/glove_metadata.tsv 95 bytes

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