Udacity - Data Analyst Nanodegree nd002 v8.0.0
WEBRip | English | MP4 | 1280 x 720 | AVC ~1389 kbps | 29.970 fps
AAC | 126 Kbps | 44.1 KHz | 2 channels | 33:13:11 | 9.77 GB
Genre: Video Tutorial
WEBRip | English | MP4 | 1280 x 720 | AVC ~1389 kbps | 29.970 fps
AAC | 126 Kbps | 44.1 KHz | 2 channels | 33:13:11 | 9.77 GB
Genre: Video Tutorial
Successful Data Analysts have a unique set of skills, and represent important value to organisations eager to make data-powered business decisions. In this program, you’ll learn to use Python, SQL, and statistics to uncover insights, communicate critical findings, and create data-driven solutions. Demand for qualified Data Analysts continues to rise, and as a graduate of this program, you will be prepared to take on these roles.Content:
Part 01-Module 01-Lesson 01_Welcome to the Nanodegree Program!
Part 01-Module 01-Lesson 02_The Life of a Data Analyst
Part 01-Module 02-Lesson 01_Project Prep SQL and Moving Averages
Part 01-Module 02-Lesson 02_Explore Weather Trends
Part 02-Module 01-Lesson 01_Numbers and Strings
Part 02-Module 01-Lesson 02_Functions, Installation and Conditionals
Part 02-Module 01-Lesson 03_Data Structures and Loops
Part 02-Module 01-Lesson 04_Files and Modules
Part 02-Module 01-Lesson 05_Wikipedia Web Crawl Case Study
Part 02-Module 02-Lesson 01_Python Project
Part 03-Module 01-Lesson 01_Anaconda
Part 03-Module 01-Lesson 02_Jupyter Notebooks
Part 03-Module 02-Lesson 01_The Data Analysis Process
Part 03-Module 02-Lesson 02_Data Analysis Process - Case Study 1
Part 03-Module 02-Lesson 03_Data Analysis Process - Case Study 2
Part 03-Module 02-Lesson 04_Programming Workflow for Data Analysis
Part 03-Module 03-Lesson 01_Basic SQL
Part 03-Module 03-Lesson 02_SQL Joins
Part 03-Module 03-Lesson 03_SQL Aggregations
Part 03-Module 03-Lesson 04_SQL Subqueries & Temporary Tables
Part 03-Module 03-Lesson 05_SQL Data Cleaning
Part 03-Module 03-Lesson 06_[Advanced] SQL Window Functions
Part 03-Module 03-Lesson 07_[Advanced] SQL Advanced JOINs & Performance Tuning
Part 03-Module 04-Lesson 01_Investigate a Dataset
Part 04-Module 01-Lesson 01_Descriptive Statistics - Part I
Part 04-Module 01-Lesson 02_Descriptive Statistics - Part II
Part 04-Module 01-Lesson 03_Admissions Case Study
Part 04-Module 01-Lesson 04_Probability
Part 04-Module 01-Lesson 05_Binomial Distribution
Part 04-Module 01-Lesson 06_Conditional Probability
Part 04-Module 01-Lesson 07_Bayes Rule
Part 04-Module 01-Lesson 08_Python Probability Practice
Part 04-Module 01-Lesson 09_Normal Distribution Theory
Part 04-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem
Part 04-Module 01-Lesson 11_Confidence Intervals
Part 04-Module 01-Lesson 12_Hypothesis Testing
Part 04-Module 01-Lesson 13_Case Study AB tests
Part 04-Module 01-Lesson 14_Regression
Part 04-Module 01-Lesson 15_Multiple Linear Regression
Part 04-Module 01-Lesson 16_Logistic Regression
Part 04-Module 02-Lesson 01_Analyze AB Test Results
Part 05-Module 01-Lesson 01_Congratulations & Next Steps
Part 06-Module 01-Lesson 01_Welcome to Term 2!
Part 06-Module 02-Lesson 01_Statistics and Programming Exercises
Part 06-Module 02-Lesson 02_Test a Perceptual Phenomenon
Part 07-Module 01-Lesson 01_What is EDA
Part 07-Module 01-Lesson 02_R Basics
Part 07-Module 01-Lesson 03_Explore One Variable
Part 07-Module 01-Lesson 04_Problem Set Explore One Variable
Part 07-Module 01-Lesson 05_Explore Two Variables
Part 07-Module 01-Lesson 06_Problem Set Explore Two Variables
Part 07-Module 01-Lesson 07_Explore Many Variables
Part 07-Module 01-Lesson 08_Problem Set Explore Many Variables
Part 07-Module 01-Lesson 09_Diamonds & Price Predictions
Part 07-Module 02-Lesson 01_Explore and Summarize Data
Part 08-Module 01-Lesson 01_Introduction to Data Wrangling
Part 08-Module 02-Lesson 01_Gathering Data
Part 08-Module 03-Lesson 01_Assessing Data
Part 08-Module 04-Lesson 01_Cleaning Data
Part 08-Module 05-Lesson 01_Wrangle and Analyze Data
Part 09-Module 01-Lesson 01_Introduction to Data Visualization
Part 09-Module 01-Lesson 02_Design
Part 09-Module 01-Lesson 03_Data Visualizations in Tableau
Part 09-Module 01-Lesson 04_Making Dashboards & Stories in Tableau
Part 09-Module 02-Lesson 01_Create a Tableau Story
Part 10-Module 01-Lesson 01_Congratulations & Next Steps
Part 11-Module 01-Lesson 01_What is Version Control
Part 11-Module 01-Lesson 02_Create A Git Repo
Part 11-Module 01-Lesson 03_Review a Repo's History
Part 11-Module 01-Lesson 04_Add Commits To A Repo
Part 11-Module 01-Lesson 05_Tagging, Branching, and Merging
Part 11-Module 01-Lesson 06_Undoing Changes
Part 12-Module 01-Lesson 01_GitHub Review
Part 13-Module 01-Lesson 01_Develop Your Personal Brand
Part 13-Module 01-Lesson 02_LinkedIn Review
Part 13-Module 01-Lesson 03_Udacity Professional Profile
Part 14-Module 01-Lesson 01_Conduct a Job Search
Part 14-Module 02-Lesson 01_Refine Your Entry-Level Resume
Part 14-Module 02-Lesson 02_Refine Your Career Change Resume
Part 14-Module 02-Lesson 03_Refine Your Prior Industry Experience Resume
Part 14-Module 03-Lesson 01_Craft Your Cover Letter
Part 15-Module 01-Lesson 01_Ace Your Interview
Part 15-Module 01-Lesson 02_Practice Behavioral Questions
Part 15-Module 01-Lesson 03_Interview Fails
Part 15-Module 01-Lesson 04_Land a Job Offer
Part 15-Module 01-Lesson 05_Interview Practice
Part 15-Module 02-Lesson 01_Introduction and Efficiency
Part 15-Module 02-Lesson 02_List-Based Collections
Part 15-Module 02-Lesson 03_Searching and Sorting
Part 15-Module 02-Lesson 04_Maps and Hashing
Part 15-Module 02-Lesson 05_Trees
Part 15-Module 02-Lesson 06_Graphs
Part 15-Module 02-Lesson 07_Case Studies in Algorithms
Part 15-Module 02-Lesson 08_Technical Interview - Python
Part 16-Module 01-Lesson 01_Welcome to Machine Learning
Part 16-Module 01-Lesson 02_Naive Bayes
Part 16-Module 01-Lesson 03_SVM
Part 16-Module 01-Lesson 04_Decision Trees
Part 16-Module 01-Lesson 05_Choose Your Own Algorithm
Part 16-Module 01-Lesson 06_Datasets and Questions
Part 16-Module 01-Lesson 07_Regressions
Part 16-Module 01-Lesson 08_Outliers
Part 16-Module 01-Lesson 09_Clustering
Part 16-Module 01-Lesson 10_Feature Scaling
Part 16-Module 01-Lesson 11_Text Learning
Part 16-Module 01-Lesson 12_Feature Selection
Part 16-Module 01-Lesson 13_PCA
Part 16-Module 01-Lesson 14_Validation
Part 16-Module 01-Lesson 15_Evaluation Metrics
Part 16-Module 01-Lesson 16_Tying It All Together
Part 17-Module 01-Lesson 01_Matrix Math and NumPy Refresher
Part 18-Module 01-Lesson 01_Why Python Programming
Part 18-Module 01-Lesson 02_Data Types and Operators
Part 18-Module 01-Lesson 03_Control Flow
Part 18-Module 01-Lesson 04_Functions
Part 18-Module 01-Lesson 05_Scripting
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