Use Python for Analyzing Visualizing and Presenting Data: Use Python for Analyzing, Visualizing and Presenting Data
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106 Lectures
20h 57m
Prepare for your Microsoft examination with our training course. The No_code course contains a complete batch of videos that will provide you with profound and thorough knowledge related to Microsoft certification exam. Pass the Microsoft No_code test with flying colors.
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Curriculum For This Course
- 1. Installation Setup and Overview 7m
- 2. IDEs and Course Resources 11m
- 3. iPython/Jupyter Notebook Overview 15m
- 1. Creating arrays 7m
- 2. Using arrays and scalars 5m
- 3. Indexing Arrays 14m
- 4. Array Transposition 4m
- 5. Universal Array Function 6m
- 6. Array Processing 22m
- 7. Array Input and Output 8m
- 1. Series 14m
- 2. DataFrames 18m
- 3. Index objects 5m
- 4. Reindex 16m
- 5. Drop Entry 6m
- 6. Selecting Entries 10m
- 7. Data Alignment 10m
- 8. Rank and Sort 6m
- 9. Summary Statistics 23m
- 10. Missing Data 12m
- 11. Index Hierarchy 14m
- 1. Reading and Writing Text Files 10m
- 2. JSON with Python 4m
- 3. HTML with Python 5m
- 4. Microsoft Excel files with Python 4m
- 1. Merge 21m
- 2. Merge on Index 13m
- 3. Concatenate 9m
- 4. Combining DataFrames 10m
- 5. Reshaping 8m
- 6. Pivoting 6m
- 7. Duplicates in DataFrames 6m
- 8. Mapping 4m
- 9. Replace 3m
- 10. Rename Index 6m
- 11. Binning 6m
- 12. Outliers 7m
- 13. Permutation 5m
- 1. GroupBy on DataFrames 18m
- 2. GroupBy on Dict and Series 13m
- 3. Aggregation 13m
- 4. Splitting Applying and Combining 10m
- 5. Cross Tabulation 5m
- 1. Installing Seaborn 2m
- 2. Histograms 9m
- 3. Kernel Density Estimate Plots 26m
- 4. Combining Plot Styles 6m
- 5. Box and Violin Plots 9m
- 6. Regression Plots 19m
- 7. Heatmaps and Clustered Matrices 17m
- 1. Data Projects Preview 3m
- 2. Intro to Data Projects 5m
- 3. Titanic Project - Part 1 17m
- 4. Titanic Project - Part 2 16m
- 5. Titanic Project - Part 3 16m
- 6. Titanic Project - Part 4 2m
- 7. Intro to Data Project - Stock Market Analysis 3m
- 8. Data Project - Stock Market Analysis Part 1 11m
- 9. Data Project - Stock Market Analysis Part 2 18m
- 10. Data Project - Stock Market Analysis Part 3 10m
- 11. Data Project - Stock Market Analysis Part 4 7m
- 12. Data Project - Stock Market Analysis Part 5 28m
- 13. Data Project - Intro to Election Analysis 2m
- 14. Data Project - Election Analysis Part 1 18m
- 15. Data Project - Election Analysis Part 2 21m
- 16. Data Project - Election Analysis Part 3 15m
- 17. Data Project - Election Analysis Part 4 26m
- 1. Introduction to Machine Learning with SciKit Learn 13m
- 2. Linear Regression Part 1 18m
- 3. Linear Regression Part 2 18m
- 4. Linear Regression Part 3 19m
- 5. Linear Regression Part 4 22m
- 6. Logistic Regression Part 1 14m
- 7. Logistic Regression Part 2 14m
- 8. Logistic Regression Part 3 12m
- 9. Logistic Regression Part 4 22m
- 10. Multi Class Classification Part 1 - Logistic Regression 19m
- 11. Multi Class Classification Part 2 - k Nearest Neighbor 23m
- 12. Support Vector Machines Part 1 13m
- 13. Support Vector Machines - Part 2 29m
- 14. Naive Bayes Part 1 10m
- 15. Naive Bayes Part 2 12m
- 16. Decision Trees and Random Forests 32m
- 17. Natural Language Processing Part 1 7m
- 18. Natural Language Processing Part 2 16m
- 19. Natural Language Processing Part 3 21m
- 20. Natural Language Processing Part 4 16m
- 1. Intro to Appendix B 3m
- 2. Discrete Uniform Distribution 6m
- 3. Continuous Uniform Distribution 7m
- 4. Binomial Distribution 13m
- 5. Poisson Distribution 11m
- 6. Normal Distribution 6m
- 7. Sampling Techniques 5m
- 8. T-Distribution 5m
- 9. Hypothesis Testing and Confidence Intervals 20m
- 10. Chi Square Test and Distribution 3m
- 11. Bayes Theorem 10m
- 1. Introduction to SQL with Python 10m
- 2. SQL - SELECT,DISTINCT,WHERE,AND & OR 10m
- 3. SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions 8m
- 1. Web Scraping Part 1 12m
- 2. Web Scraping Part 2 12m
- 1. Python Overview Part 1 19m
- 2. Python Overview Part 2 12m
- 3. Python Overview Part 3 10m
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