Udacity – Become a Data Analyst 2018-12
Udacity – Become a Data Analyst 2018-12 Downloadly IRSpace
Become a Data Analyst، This program prepares learners for a career as a data analyst by helping them learn to organize data, uncover patterns and insights, draw meaningful conclusions, and clearly communicate critical findings. Learners will develop proficiency in Python and its data analysis libraries (Numpy, pandas, Matplotlib) and SQL as they build a portfolio of projects to showcase in their job search. Depending on how quickly learners work through the material, the amount of time required is variable. We have included an hourly estimation for each section of the program.
The program covers one term of three month (approx. 13 weeks). If learners spend about 10 hours per week working through the program, they should finish the term within 13 weeks. Learners will have an additional four weeks beyond the end of the term to complete all projects. In order to succeed in this program, we recommend having experience working with data in Python (Numpy and Pandas) and SQL.
What you’ll learn
- Programming Workflow for Data Analysis
- Simpson’s Paradox
- Binomial Distribution
- Conditional Probability
- Bayes Rule
- Sampling Distributions & Central Limit Theorem
- Introduction to Data Analysis
- Practical Statistics
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Data Wrangling
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Data Visualization with Python
Who this course is for
- If you’re someone who wants to make data driven decisions or work with various types of data to conduct analyses, or is interested in becoming an data analyst, this program is ideal for you, because you’ll learn applied statistics, data wrangling with Python, and data visualization with Matplotlib, which will enable you to work with any data set and find and showcase meaningful insights.
Specificatoin of Become a Data Analyst
- Publisher : Udacity
- Teacher : Josh Bernhard , Sebastian Thrun , Derek Steer , Juno Lee , Mike Yi , David Venturi , Sam Nelson
- Language : English
- Level : Intermediate
- Number of Course : 121
- Duration : 33 hours and 13 minutes
Content of Become a Data Analyst
# Welcome to Term 1!
# Introduction to Python
# Introduction to Data Analysis
# Practical Statistics
# Congratulations and Next Steps
# Welcome to Term 2!
# Exploratory Data Analysis
# Data Wrangling
# Data Story Telling
# Congratulations and Next Steps
# (Elective) How to use Git and GitHub
# (Elective) Career: GitHub Profile Review
# (Elective) Career: Networking
# (Elective) Career: Job Search Strategies
# (Elective) Career: Data Analyst Interview Practice
# (Elective) Intro to Machine Learning
# (Elective) Matrix Math and Numpy Refresher
# (Elective) [New] Introduction to Python
# (Elective) Introduction to Python
Requirements
- Python standard libraries
- Working with data with Pandas and NumPy
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Subtitle : English
Quality: 720p
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