What kind of people are best suited for roles in data science?

People who are best suited for working in data science have a strong mix of technical skills and complex problem-solving skills. Beyond the job-related skills, people should have strong critical reasoning abilities, which are needed to help them analyze data and solve problems. Creativity, attention to detail, and strong communication skills allow data scientists to translate their analytical findings into actions that business leaders and decision-makers can take. Because this field continues evolving, people in data science should also be enthusiastic about learning new things and willing to constantly expand their skills.

How do I know if learning data science is right for me?

Are you passionate about using data to solve complex problems? Do you enjoy working in both the business and technology fields? Do you have a thirst for learning new things? If you can answer yes to any or all of those questions, learning data science may well be an ideal course for you. Additionally, if you're looking for a field that's in high demand and applicable to a variety of potential positions, it's hard to top data science. It's among the fastest-growing fields, and by 2026 it's predicted to create more than 11 million new jobs, according to the Bureau of Labor Statistics .

What are common career paths for someone in data science?

Data science opens up a variety of potential career paths, including data scientist, machine learning engineer, data architect, and business intelligence developer. Most people who work in data science start with entry-level jobs like junior data scientist or data analyst after earning a bachelor's degree in computer science or a related field. Some people work their way up from entry-level jobs. Others pursue certifications or trainings specific to systems. To access the largest pool of opportunities, you might want to get a master's or doctoral degree in information technology or computer science.

What types of places hire people with a background in data science?

Data scientists work in a variety of industries, including big tech companies like Google and IBM, financial organizations, pharmaceutical companies, retailers, and even fashion houses. Data scientists work on many different types of jobs, which makes their work valuable to many different types of industries. For example, data scientists might work in fraud identification, market analysis, or manufacturing analysis. Or they might work on projects that task them with analyzing large amounts of data and putting it into reports and dashboards to help stakeholders better understand the significance. Data science can be helpful for marketing, sales, and so much more.

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IBM Skills Network
Introduction to Data Science
Habilidades que obtendrás: Data Science, Data Structures, SQL, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Statistical Programming, Databases, Python Programming, Database Theory, Data Visualization Software, R Programming, Data Management, Data Mining, Regression, Devops Tools, Machine Learning Algorithms, SPSS, Basic Descriptive Statistics, Data Analysis, Database Application, Big Data, Computer Programming, Database Administration, Deep Learning, General Statistics, Machine Learning, Marketing, Probability & Statistics, Storytelling, Writing
4.6
(78.3k reseñas)
Beginner · Specialization · 3-6 Months
Gratis
Gratis
Eindhoven University of Technology
Process Mining: Data science in Action
Habilidades que obtendrás: Business Analysis, Process Analysis, Data Analysis, Data Mining, Machine Learning, Machine Learning Algorithms, Algorithms, Business Process Management, Business Psychology, Communication, Data Management, Data Structures, Entrepreneurship, Leadership and Management, Organizational Development, Strategy and Operations, Theoretical Computer Science
4.7
(1.1k reseñas)
Intermediate · Course · 1-3 Months
IBM Skills Network
IBM Data Science
Habilidades que obtendrás: Python Programming, Data Science, Data Analysis, Data Structures, Statistical Programming, Machine Learning, Data Mining, Regression, Machine Learning Algorithms, Data Visualization, General Statistics, Basic Descriptive Statistics, SQL, Applied Machine Learning, Statistical Analysis, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Databases, Programming Principles, Exploratory Data Analysis, Computer Programming, Statistical Visualization, Algebra, Data Management, Database Theory, Data Visualization Software, R Programming, Statistical Machine Learning, Statistical Tests, Deep Learning, Probability & Statistics, Extract, Transform, Load, Plot (Graphics), Devops Tools, SPSS, Estimation, Interactive Data Visualization, Algorithms, Database Application, Geovisualization, Reinforcement Learning, Theoretical Computer Science, Big Data, Business Analysis, Computational Logic, Correlation And Dependence, Database Administration, Econometrics, Entrepreneurship, Marketing, Mathematical Theory & Analysis, Mathematics, Spreadsheet Software, Storytelling, Supply Chain Systems, Supply Chain and Logistics, Writing
4.6
(108k reseñas)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Analyst
Habilidades que obtendrás: Data Analysis, Python Programming, Data Visualization, Exploratory Data Analysis, Basic Descriptive Statistics, Data Structures, Statistical Programming, Data Science, Statistical Visualization, Plot (Graphics), Data Management, General Statistics, SQL, Databases, Business Analysis, Microsoft Excel, Spreadsheet Software, Data Mining, Statistical Analysis, Programming Principles, Probability & Statistics, Regression, Machine Learning, Algebra, Computer Programming, Data Analysis Software, Database Theory, Probability Distribution, Applied Machine Learning, Statistical Tests, Big Data, Correlation And Dependence, Data Visualization Software, Estimation, NoSQL, Geovisualization, ArcGIS, Cloud Computing, Data Warehousing, Database Application, Extract, Transform, Load, HTML and CSS, Knitr, Mathematics, Minitab, PostgreSQL, R Programming, SAS (Software), SPSS, Apache, Computational Logic, Computer Programming Tools, Database Administration, Econometrics, Interactive Data Visualization, Leadership and Management, Mathematical Theory & Analysis, Operating Systems, Professional Development, Statistical Machine Learning, System Programming, Theoretical Computer Science
4.6
(62.3k reseñas)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Engineering
Habilidades que obtendrás: Data Management, Databases, Data Architecture, Data Structures, Big Data, Database Theory, SQL, Apache, Database Administration, Extract, Transform, Load, Python Programming, Data Model, Database Application, Data Warehousing, Data Analysis, NoSQL, Data Engineering, Distributed Computing Architecture, Database Design, Operating Systems, System Programming, System Software, Programming Principles, Statistical Programming, Algebra, Computer Architecture, PostgreSQL, Applied Machine Learning, Correlation And Dependence, Feature Engineering, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Regression, Statistical Analysis, Statistical Machine Learning, Data Visualization, Data Visualization Software, Basic Descriptive Statistics, Exploratory Data Analysis, Cloud Applications, Cloud Computing, Data Science, DevOps, Kubernetes, Leadership and Management, Network Architecture, Network Security, Other Programming Languages, Professional Development, Security Engineering, Algorithms, Computational Logic, Computational Thinking, Computer Networking, Computer Programming, Computer Programming Tools, IBM Cloud, Linux, Mathematical Theory & Analysis, Mathematics, Microarchitecture, Project Management, Security Strategy, Software Architecture, Software Engineering, Strategy and Operations, Theoretical Computer Science
4.6
(41.2k reseñas)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Analytics with Excel and R
Habilidades que obtendrás: Data Analysis, R Programming, Data Visualization, Plot (Graphics), Data Management, SQL, Exploratory Data Analysis, Data Mining, Databases, Basic Descriptive Statistics, General Statistics, Data Visualization Software, Statistical Programming, Data Analysis Software, Interactive Data Visualization, Statistical Visualization, Statistical Analysis, Big Data, Business Analysis, Microsoft Excel, Probability & Statistics, Spreadsheet Software, Database Theory, Regression, Statistical Tests, Data Science, Data Structures, Software Visualization, Machine Learning, User Experience, Probability Distribution, NoSQL, Python Programming, Applied Machine Learning, Deep Learning, Estimation, Geovisualization, Linear Algebra, Machine Learning Algorithms, Machine Learning Software, SAS (Software), Spatial Data Analysis, Statistical Machine Learning, Cloud Computing, Data Architecture, Data Model, Data Warehousing, Database Administration, Database Application, Database Design, Mathematics, Visualization (Computer Graphics), Accounting, Advertising, Apache, Communication, Computational Logic, Computer Programming, Extract, Transform, Load, Leadership and Management, Marketing, Operating Systems, Professional Development, Programming Principles, System Programming, Theoretical Computer Science
4.7
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IBM Skills Network
Applied Software Engineering Fundamentals
Habilidades que obtendrás: Software Engineering, Python Programming, Data Analysis, Data Structures, Programming Principles, Computer Programming, Software Engineering Tools, Web Development, Algebra, Operating Systems, Other Web Frameworks, System Programming, System Software, Agile Software Development, Front-End Web Development, Application Development, Basic Descriptive Statistics, Design and Product, Exploratory Data Analysis, Full-Stack Web Development, Leadership and Management, Professional Development, Software Architecture, Software Framework, Theoretical Computer Science, Web Development Tools, Communication, Computational Logic, Journalism, Linux, Mathematical Theory & Analysis, Mathematics, Software Testing, Statistical Programming, Systems Design
4.6
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Búsquedas relacionadas con applied data science

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En síntesis, estos son los 10 cursos más populares applied data science

Заключительный курс по теме «Прикладная наука о данных»: IBM Skills Network
Applied Calculus with Python: Johns Hopkins University
Master of Science in Applied Data Analytics: Queen Mary, University of London
Introduction to Data Science: IBM Skills Network
Making Data Science Work for Clinical Reporting: Genentech
Player Evaluation, Team Performance and Roster Management: The State University of New York
Process Mining: Data science in Action: Eindhoven University of Technology
IBM Data Science: IBM Skills Network
IBM Data Analyst: IBM Skills Network
IBM Data Engineering: IBM Skills Network

Preguntas frecuentes sobre Applied Data Science

People who are best suited for working in data science have a strong mix of technical skills and complex problem-solving skills. Beyond the job-related skills, people should have strong critical reasoning abilities, which are needed to help them analyze data and solve problems. Creativity, attention to detail, and strong communication skills allow data scientists to translate their analytical findings into actions that business leaders and decision-makers can take. Because this field continues evolving, people in data science should also be enthusiastic about learning new things and willing to constantly expand their skills.‎
Are you passionate about using data to solve complex problems? Do you enjoy working in both the business and technology fields? Do you have a thirst for learning new things? If you can answer yes to any or all of those questions, learning data science may well be an ideal course for you. Additionally, if you're looking for a field that's in high demand and applicable to a variety of potential positions, it's hard to top data science. It's among the fastest-growing fields, and by 2026 it's predicted to create more than 11 million new jobs, according to the Bureau of Labor Statistics.‎
Data science opens up a variety of potential career paths, including data scientist, machine learning engineer, data architect, and business intelligence developer. Most people who work in data science start with entry-level jobs like junior data scientist or data analyst after earning a bachelor's degree in computer science or a related field. Some people work their way up from entry-level jobs. Others pursue certifications or trainings specific to systems. To access the largest pool of opportunities, you might want to get a master's or doctoral degree in information technology or computer science.‎
Data scientists work in a variety of industries, including big tech companies like Google and IBM, financial organizations, pharmaceutical companies, retailers, and even fashion houses. Data scientists work on many different types of jobs, which makes their work valuable to many different types of industries. For example, data scientists might work in fraud identification, market analysis, or manufacturing analysis. Or they might work on projects that task them with analyzing large amounts of data and putting it into reports and dashboards to help stakeholders better understand the significance. Data science can be helpful for marketing, sales, and so much more.‎

Se puso a disposición este contenido de preguntas frecuentes solo con fines informativos. Se les pide a los estudiantes que realicen investigaciones adicionales para asegurarse de que los cursos y otras credenciales cumplan con sus objetivos personales, profesionales y financieros.