Data Science: Machine Learning, Data Mining, BI, Business Analytics
What is Data Science?
Data science is the process of collecting, processing, understanding, and communicating meaning from data. As a field of study, data science involves programming, statistics, algorithms, and visualizations. It also involves effectively conveying meaning and value from data.
The data science lifecycle involves business or organization-level understanding of goals, what data is available, data preparation, data analysis, data modeling, data evaluation, and model deployment (or communication of results). Following the data life cycle is a good way of organizing goals for an organization or business while getting the best value from data resources.
Data scientists are necessary for almost any modern business and require high technical and math skills. Data scientists must be able to analyze data and make meaning from it complexly. Data scientists can answer questions and create possible solutions to existing organizational problems.
Data science requires skills found in similar computer science roles, like programming and math. Additionally, data scientists must be creative, know how to build models, and have good communication skills to communicate results effectively to a team. Data science uses tools like SQL, GitHub, R, Python, and many others. Data science is a high-demand career, and the demand for people in this role is only expected to grow.
While being a data scientist can be a demanding role, one can learn this field in under a year. This experience takes dedicated study time but is manageable for the motivated learner. By committing to studying data science with the same hours as a full-time job, one can learn the basics to become an entry-level data scientist.
Data Science Topics
Learn about artificial intelligence. Understand what artificial intelligence is, learn its history and evolution, and see examples of artificial intelligence.
Learn what big data is and understand its different types. Explore the applications of big data. Discover big data examples and see their characteristics.
Explore what data analysis is. Learn the definition of data analysis. Understand the process of data analysis. Know how to explain a data analysis report.
Find out what data visualization is, and understand its key purposes. Explore different types of data visualization, and discover data visualization examples.
Statistical Experimental Design
Learn about different types of experimental designs in statistics, including examples. Explore the various steps of the experimental process with examples.
Data Science Resources
The resources you can find at study.com will be helpful for the dedicated learner's journey toward becoming a data scientist. At Study.com, one can find multiple resources about the data sciences. Study.com can help study the role of data scientists and what tools for success are necessary.
Courses for Learning Data Science
Multiple courses at study.com about data science specializations are available. This data science curriculum supports the basics of data science, database programming, database management, and algorithms. Study.com offers data science courses, including an introductory programming course in the SQL language.
Analytics 103: Intro to Relational Databases & SQL
Analytics 103 is a college-level course recommended for credit. Topics of study include an introduction to databases and database management systems. Lessons also include the basics of SQL programming language, such as syntax, queries, and modifying data.
Computer Science 107: Database Fundamentals
Computer Science 107 is recommended for college credit. Exciting lesson topics include introducing databases and the relational database model. Lessons continue in SQL, including data types, variations, relations, modeling and design, and more.
Computer Science 201: Data Structures & Algorithms
Computer Science 201 introduces the basics of Java. Students will learn how to program an environment in Java and additional topics such as core data structures, algorithms, trees, sorting, text processing, graph data, and more. College credit eligible.
Computer Science 204: Database Programming
This database programming course will cover learning topics such as creating and managing databases, populating and retrieving data, manipulating data, data queries in multiple tables, modifying tables, and more. Eligible for college credit.
Computer Science 303: Database Management
Computer Science 303 covers database technology, database management systems, and their functions, database types and uses, the design process, administrative procedures, SQL databases, and more. This course is recommended for college credit.
Frequently Asked Questions
Does data science require coding?
Data science does require at least some coding. Data scientists use computers and programming to collect and process data, which requires the knowledge and skills of a basic level of coding in a programming language.
Can someone learn data science in one year?
Dedicated people can learn the basics of data science in one year or less. It would require that one study hard and dedicate study hours comparable to that of a full-time job to gain the knowledge and skills required of an entry-level data scientist.
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