What you'll learn
Working knowledge of Data Science Tools such as Jupyter Notebooks, R Studio, GitHub, Watson Studio
Python programming basics including data structures, logic, working with files, invoking APIs, and libraries such as Pandas and Numpy
Statistical Analysis techniques including Descriptive Statistics, Data Visualization, Probability Distribution, Hypothesis Testing and Regression
Relational Database fundamentals including SQL query language, Select statements, sorting & filtering, database functions, accessing multiple tables
Skills you'll gain
Probability And Statistics
Basic Descriptive Statistics
Statistical Hypothesis Testing
Data Visualization
Regression Analysis
Data Science
Data Analysis
Python Programming
Numpy
Pandas
Jupyter notebooks
Cloud Databases
Relational Database Management System (RDBMS)
SQL
Github
Rstudio
Data Science is one of the hottest professions of the decade, and the demand for data scientists who can analyze data and communicate results to inform data driven decisions has never been greater. This Specialization from IBM will help anyone interested in pursuing a career in data science by teaching them fundamental skills to get started in this in-demand field.
The specialization consists of 5 self-paced online courses that will provide you with the foundational skills required for Data Science, including open source tools and libraries, Python, Statistical Analysis, SQL, and relational databases. You'll learn these data science pre-requisites through hands-on practice using real data science tools and real-world data sets.
Upon successfully completing these courses, you will have the practical knowledge and experience to delve deeper in Data Science and work on more advanced Data Science projects.
No prior knowledge of computer science or programming languages required.
This program is ACE® recommended—when you complete, you can earn up to 8 college credits.
Applied Learning Project
All courses in the specialization contain multiple hands-on labs and assignments to help you gain practical experience and skills with a variety of data sets. Build your data science portfolio from the artifacts you produce throughout this program. Course-culminating projects include
Extracting and graphing financial data with the Pandas data analysis Python library
Generating visualizations and conducting statistical tests to provide insight on housing trends using census data
Using SQL to query census, crime, and demographic data sets to identify causes that impact enrollment, safety, health, and environment ratings in schools
Homepage

https://www.coursera.org/specializations/data-science-fundamentals-python-sql

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