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Course Content
1. Introduction
0/1
1.1. Course Intro
03:53
2. Setup
0/3
2.1. Installation Setup and Overview
07:17
2.2. IDEs and Course Resources
10:56
2.3. iPython/Jupyter Notebook Overview
14:58
3. Learning Numpy
0/8
3.1. Intro to Numpy
3.2. Create Arrays
07:28
3.3. Using Arrays and Scalars
04:42
3.4. Indexing Arrays
14:20
3.5. Array Transposition
04:08
3.6. Universal Arrays Function
06:05
3.7. Array Processing
21:49
3.8. Array Input and Output
08:00
4. Learning Pandas
0/11
4.1. Series
13:59
4.2. Data Frames
17:47
4.3. Index Objects
05:00
4.4. Reindex
15:52
4.5. Drop Entry
05:42
4.6. Selecting Entries
10:23
4.7. Data Alignment
10:15
4.8. Rank and Sort
05:38
4.9. Summary Statistics
22:36
4.10. Missing Data
11:38
4.11. Index Hierarchy
13:29
5. Working with Data: Part 1
0/4
5.1. Reading and Writing Text Files
10:03
5.2. JSON with Python
04:12
5.3. HTML with Python
04:36
5.4. Microsoft Excel Files with Python
03:52
6. Working with Data: Part 2
0/13
6.1. Merge
20:32
6.2. Merge on Index
12:37
6.3. Concatenate
09:20
6.4. Combining Data Frames
10:19
6.5. Reshaping
07:51
6.6. Pivoting
05:31
6.7. Duplicates in Data Frames
05:55
6.8. Mapping
04:13
6.9. Replace
03:16
6.10. Rename Index
05:53
6.11. Binning
06:17
6.12. Outliners
06:53
6.13. Permutation
05:22
7. Working with Data: Part 3
0/5
7.1. Group by on Data Frames
17:42
7.2. Group by on Dict and Series
13:22
7.3. Aggregation
12:41
7.4. Splitting Applying and Combining
10:03
7.5. Cross Tabulation
05:07
8. Data Visualization
0/7
8.1. Installing Seaborn
01:44
8.2. Histograms
09:19
8.3. Kernel Density Estimate Plots
25:59
8.4. Combining Plot Styles
06:15
8.5. Box and Violin Plots
08:51
8.6. Regression Plots
18:40
8.7. Heatmaps and Clustered Matrices
16:47
9. Example Project
0/17
9.1. Data Project Preview
03:03
9.2. Intro to Data Projects
04:34
9.3. Titanic Project – Part 1
17:07
9.4. Titanic Project – Part 2
16:08
9.5. Titanic Project – Part 3
15:48
9.6. Titanic Project – Part 4
02:02
9.7. Intro to Data Project – Stock Market Analysis
03:10
9.8. Data Project – Stock Market Analysis Part 1
11:20
9.9. Data Project – Stock Market Analysis Part 2
18:07
9.10. Data Project – Stock Market Analysis Part 3
10:25
9.11. Data Project – Stock Market Analysis Part 4
06:57
9.12. Data Project – Stock Market Analysis Part 5
27:41
9.13. Data Project – Intro to Election Analysis
02:21
9.14. Data Project – Election Analysis Part 1
18:00
9.15. Data Project – Election Analysis Part 2
20:35
9.16. Data Project – Election Analysis Part 3
15:05
9.17. Data Project – Election Analysis Part 4
25:58
10. Machine Learning
0/20
10.1. Introduction to Machine Learning with SciKit Learn
12:52
10.2. Linear Regression Part 1
17:40
10.3. Linear Regression Part 2
18:21
10.4. Linear Regression Part 3
18:46
10.5. Linear Regression Part 4
22:09
10.6. Logistic Regression Part 1
14:19
10.7. Logistic Regression Part 2
14:26
10.8. Logistic Regression Part 3
12:21
10.9. Logistic Regression Part 4
22:23
10.10. Multi Class Classification Part 1 – Logistic Regression
18:34
10.11. Multi Class Classification Part 2 – K Nearest Neighbor
23:06
10.12. Support Vector Machines – Part 1
12:53
10.13. Support Vector Machines – Part 2
29:08
10.14. Naive Bayes – Part 1
10:04
10.15. Naive Bayes – Part 2
12:26
10.16. Decision Trees and Random Forests
31:48
10.17. Natural Language Processing – Part 1
07:21
10.18. Natural Language Processing – Part 2
15:40
10.19. Natural Language Processing – Part 3
20:48
10.20. Natural Language Processing – Part 4
16:17
11. Statistics Overview
0/11
11.1. Introduction
02:40
11.2. Discrete Uniform Distribution
06:06
11.3. Continuous Uniform Distribution
06:57
11.4. Binomial Distribution
12:31
11.5. Poisson Distribution
10:39
11.6. Normal Distribution
06:25
11.7. Sampling Techniques
04:51
11.8. T-Distribution
05:08
11.9. Hypothesis Testing and Confidence Intervals
20:09
11.10. Chi Square Test and Distribution
02:54
11.11. Bayes Theorem
10:03
12. SQL and Python
0/3
12.1. Introduction to SQL with Python
10:00
12.2. SQL – SELECT,DISTINCT,WHERE,AND & OR
09:59
12.3. SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions
08:26
13. Web Scraping with Python
0/2
13.1. Web Scraping – Part 1
12:15
13.2. Web Scraping – Part 2
12:15
14. Python Special Offers
0/3
14.1. Python Overview – Part 1
18:52
14.2. Python Overview – Part 2
12:19
14.3. Python Overview – Part 3
10:10
Python for Data Analysis and Visualization
About Lesson
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