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How to Learn about Data Science

Data Science Courses

For a list of Data Science programs across the United States, offered by major universities and colleges, check out this data visualization. The table below shows some of the most popular online/in-person offerings for those wishing to do it on their own. Many colleges and universities offer similar programs, often through statistics or business departments, so check with your local universities and professors to see if there are any local offerings that can help meet data science needs.

CourseProvided ThroughDeveloped ByPriceFormat
Data Science SpecializationCourseraJohns Hopkins University$441Online
Executive Data Science SpecializationCourseraJohns Hopkins UniversityFrom $49/courseOnline
Master of Computer Science in Data ScienceCourseraUniversity of Illinois at Urbana-Champaign$19,000 for 32 credit hour degreeOnline
Data Science at ScaleCourseraUniversity of Washington$284Online
Intro to Data ScienceUDACITYUDACITYFreeOnline
Applied Data Science: An IntroductionCourse CentralSyracuse UniversityFreeOnline
Open Source SocietyOpen Source Society UniversityGithubFreeOnline
Data Science ImmersiveGeneral AssemblyGeneral Assembly$14,500In Person
Data Science Part TimeGeneral AssemblyGeneral Assembly$4,000½ Online ½ In Person

Data Science Concepts

Not everyone wants to be a Data Scientist, but plenty of people want to strengthen their skills in the underlying competencies. It’s possible to learn key concepts in data science without going through a full-fledged program like those mentioned above. For a high-level overview of some key (and commonly confusing) terms, check out the GovEx Data Science Cheat Sheet. The list below includes the subject areas which are often taught in data science coursework.

The internet is rich with resources for learning data science. Plus, the community is an active one so join in and get involved! You can liberally use sites like Stack Overflow, R Bloggers, GitHub, and even Twitter to start learning from your peers, no matter your skill level as a data scientist.

Getting and Cleaning DataConceptAcquiring and preparing data for analysis through a variety of manual and automated techniques.Introductory
Exploratory Data AnalysisConceptPerforming initial analysis on data without a particular research question in mind in order to discover potential insights.Intermediate
Reproducible ResearchConceptCataloguing research so that others can follow data, steps, and analysis in order to replicate/test findings.Advanced
Descriptive StatisticsStatisticsStatistics used to describe and summarize data, including measures of central tendency (mean, median, mode, etc.) and variance.Introductory
Inferential StatisticsStatisticsUsing data from a sample to make inferences about a larger population of data.Intermediate
Bayesian StatisticsStatisticsField of statistics that treats probability as a state of belief that can change given new information.Advanced
ProbabilityStatisticsA measure of the likelihood that an event will occur.Introductory
R ProgrammingProgramming LanguageA programming language used for statistical computing.Advanced
Python ProgrammingProgramming LanguageA general purpose programming language.Advanced
Regression ModelsAnalysisStatistical methods for analyzing relationships between variables.Introductory
Machine LearningConceptComputational algorithms used to make predictions.Advanced
Data VisualizationConceptThe visual representation of information in a multidimensional space.Introductory
EconometricsStatisticsA field of statistics for analyzing economic data.Advanced
Big DataConceptA term used to describe data that is extremely large in storage size, or that requires large amounts of processing to analyze.Advanced
AlgorithmsConceptA set of defined operations on a given input that result in an output.Introductory
Survey Data Collection & AnalysisConceptSurveys are a set of questions answered by a selected group of people. The answers can be analyzed quantitatively and/or qualitatively.Intermediate
Text MiningConceptMethod of computational analysis to derive information from text.Intermediate
Business IntelligenceAnalysisMethod of data analysis to produce useful information for business purposes.Intermediate
Data WarehousingConceptSystem for electronically storing data in an organized manner.Advanced
Systems (GIS)/ spatial analysisAnalysisMethod for analyzing the geographical dimension of various types of data.Advanced
SQL*DatabasesQuerying language used to interact with a relational database.Intermediate
PostgreSQL*DatabasesQuerying language for PostgreSQL relational databases.Intermediate
NoSQL*DatabasesQuerying language used to interact with a non-relational database.Advanced

Data Analysis Tools

ExcelAnalysisA Microsoft spreadsheet application used for calculation and other purposes.Introductory
RAnalysisA programming language used for statistical computing.Advanced
PythonAnalysisA general purpose programming language made with ease and accessibility in mind.Advanced
TableauAnalysisAn application used for data visualization.Intermediate
SPSSAnalysisA software package used for statistical computing.Advanced
SASAnalysisA software package used for statistical computing.Advanced

If you’re not familiar with databases, SQL, Postgre, or NoSQL, check out this fun and information introduction to databases from Guru 99.

Data Science Tools

ToolUsed forCost
GitVersion controlFree
GithubCollaborative developmentFree
R/ RStudioStatistical analysis, visualizationFree
Python/ JupyterStatistical analysis, visualization, automation, general programmingFree
ExcelStatistical analysis, data storage$
Hadoop (large datasets)Data storage, computingFree
Hive (large datasets)Data storageFree
Pig (large datasets)Data analysisFree
Apache Spark (large datasets)Data analysisFree
TableauData analysis, visualization$$$
SPSSData analysis$$
SASAnalysis, data management$$
MySQLData storageFree
PostgreSQLData storageFree

Data Science Books and Guides






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