Certification training

Use Python for Analyzing Visualizing and Presenting Data: Use Python for Analyzing, Visualizing and Presenting Data

Prepare for your exam with a structured video course built for focused study, topic review, and repeatable progress before exam day.

106Lectures
20h 57mDuration
Vendor
Use Python for Analyzing Visualizing and Presenting Data: Use Python for Analyzing, Visualizing and Presenting Data course cover Best seller
certification training 106 lessons arranged in a guided course path
Course overview

Study with a clear path.

Move through focused sections, review lecture timing, and return directly to the objectives that need more work.

Sequenced lessons

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Video-first prep

Use concise lecture blocks for technical review before moving into exam practice.

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Curriculum

Course sections.

13 sections, 106 lessons, and lecture-level duration details.

01 Installation Setup and Overview 7m
02 IDEs and Course Resources 11m
03 iPython/Jupyter Notebook Overview 15m

01 Creating arrays 7m
02 Using arrays and scalars 5m
03 Indexing Arrays 14m
04 Array Transposition 4m
05 Universal Array Function 6m
06 Array Processing 22m
07 Array Input and Output 8m

01 Series 14m
02 DataFrames 18m
03 Index objects 5m
04 Reindex 16m
05 Drop Entry 6m
06 Selecting Entries 10m
07 Data Alignment 10m
08 Rank and Sort 6m
09 Summary Statistics 23m
10 Missing Data 12m
11 Index Hierarchy 14m

01 Reading and Writing Text Files 10m
02 JSON with Python 4m
03 HTML with Python 5m
04 Microsoft Excel files with Python 4m

01 Merge 21m
02 Merge on Index 13m
03 Concatenate 9m
04 Combining DataFrames 10m
05 Reshaping 8m
06 Pivoting 6m
07 Duplicates in DataFrames 6m
08 Mapping 4m
09 Replace 3m
10 Rename Index 6m
11 Binning 6m
12 Outliers 7m
13 Permutation 5m

01 GroupBy on DataFrames 18m
02 GroupBy on Dict and Series 13m
03 Aggregation 13m
04 Splitting Applying and Combining 10m
05 Cross Tabulation 5m

01 Installing Seaborn 2m
02 Histograms 9m
03 Kernel Density Estimate Plots 26m
04 Combining Plot Styles 6m
05 Box and Violin Plots 9m
06 Regression Plots 19m
07 Heatmaps and Clustered Matrices 17m

01 Data Projects Preview 3m
02 Intro to Data Projects 5m
03 Titanic Project - Part 1 17m
04 Titanic Project - Part 2 16m
05 Titanic Project - Part 3 16m
06 Titanic Project - Part 4 2m
07 Intro to Data Project - Stock Market Analysis 3m
08 Data Project - Stock Market Analysis Part 1 11m
09 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

01 Introduction to Machine Learning with SciKit Learn 13m
02 Linear Regression Part 1 18m
03 Linear Regression Part 2 18m
04 Linear Regression Part 3 19m
05 Linear Regression Part 4 22m
06 Logistic Regression Part 1 14m
07 Logistic Regression Part 2 14m
08 Logistic Regression Part 3 12m
09 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

01 Intro to Appendix B 3m
02 Discrete Uniform Distribution 6m
03 Continuous Uniform Distribution 7m
04 Binomial Distribution 13m
05 Poisson Distribution 11m
06 Normal Distribution 6m
07 Sampling Techniques 5m
08 T-Distribution 5m
09 Hypothesis Testing and Confidence Intervals 20m
10 Chi Square Test and Distribution 3m
11 Bayes Theorem 10m

01 Introduction to SQL with Python 10m
02 SQL - SELECT,DISTINCT,WHERE,AND & OR 10m
03 SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions 8m

01 Web Scraping Part 1 12m
02 Web Scraping Part 2 12m

01 Python Overview Part 1 19m
02 Python Overview Part 2 12m
03 Python Overview Part 3 10m
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