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    Udacity - Data Analyst Nanodegree nd002 v8.0.0

    Posted By: ParRus
    Udacity - Data Analyst Nanodegree nd002 v8.0.0

    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

    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

    also You can watch my other: Programming-posts

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    Udacity - Data Analyst Nanodegree nd002 v8.0.0

    Udacity - Data Analyst Nanodegree nd002 v8.0.0

    Udacity - Data Analyst Nanodegree nd002 v8.0.0

    Udacity - Data Analyst Nanodegree nd002 v8.0.0

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    Udacity - Data Analyst Nanodegree nd002 v8.0.0