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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University of Colorado Boulder
Master of Engineering in Engineering Management
Habilidades que obtendrás: Theoretical Computer Science, Probability & Statistics, General Statistics, Algorithms, Data Management, Strategy and Operations, Computer Architecture, Mathematics, Leadership and Management, Databases, Data Analysis, Communication, Hardware Design, Operating Systems, Statistical Programming, Computer Programming, Machine Learning, Research and Design, Business Analysis, Finance, Regression, SQL, Writing, Project Management, Data Structures, Statistical Analysis, Business Communication, Entrepreneurship, Experiment, Probability Distribution, Software Engineering, Database Design, Statistical Tests, Computer Networking, Accounting, Computer Graphics, Design and Product, Systems Design, Data Visualization, Data Model, Database Administration, Database Application, Database Theory, Machine Learning Algorithms, Operations Research, Statistical Machine Learning, Human Computer Interaction, Estimation, Internet Of Things, PostgreSQL, Problem Solving, Graph Theory, Network Architecture, Applied Mathematics, Computer Vision, Deep Learning, Programming Principles, Geometry, User Experience, Econometrics, Marketing, Mathematical Theory & Analysis, Python Programming, Supply Chain and Logistics, Computer Graphic Techniques, Algebra, Cryptography, Business Psychology, Interactive Design, Budget Management, Correlation And Dependence, Distributed Computing Architecture, Financial Analysis, Linear Algebra, Linux, Critical Thinking, Security Engineering, Data Mining, Cost Accounting, Differential Equations, User Experience Design, Data Warehousing, Network Model, Cloud Computing, Cyberattacks, Computer Programming Tools, Computational Logic, Applied Machine Learning, Calculus, Computational Thinking, Feature Engineering, Graphic Design, Investment Management, Other Programming Languages, Sales, Scrum (Software Development), Software Architecture, Software Testing, System Programming, Visual Design, Human Resources, Matlab, Artificial Neural Networks, Emotional Intelligence, Market Analysis, NoSQL, Statistical Visualization, Basic Descriptive Statistics, C Programming Language Family, Data Analysis Software, Exploratory Data Analysis, FinTech, Material Handling, Organizational Development, Product Lifecycle, Risk Management, Strategy, Amazon Web Services, Big Data, Cloud Platforms, Culture, Decision Making, Graphics Software, Microarchitecture, Security Strategy, Application Development, Computer Security Models, Leadership Development, Operational Analysis, Product Design, Reinforcement Learning, Software Security, System Security, User Research, Market Research, Plot (Graphics), R Programming, Account Management, Banking, BlockChain, Business Process Management, Contract Management, Data Architecture, Financial Accounting, Financial Management, Generally Accepted Accounting Principles (GAAP), Geovisualization, Inventory Management, Management Accounting, Markov Model, Natural Language Processing, Operations Management, Planning, Product Management, Spreadsheet Software, Storytelling, Supplier Relationship Management, Benefits, Collaboration, Computer Science, Computer Security Incident Management, Data Science, Dimensionality Reduction, Forecasting, Journalism, Negotiation, Network Analysis, Network Security, Resilience, System Software
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Degree · 1-4 Years
University of Colorado Boulder
Engineering Management Graduate Certificate
Habilidades que obtendrás: Leadership and Management, Finance, Strategy and Operations, Project Management, Accounting, Entrepreneurship, Budget Management, Business Analysis, Data Analysis, Financial Analysis, Communication, Cost Accounting, Scrum (Software Development), Software Engineering, Emotional Intelligence, Investment Management, Marketing, Supply Chain and Logistics, Sales, Strategy, Risk Management, Business Psychology, FinTech, Organizational Development, Human Resources, Leadership Development, Generally Accepted Accounting Principles (GAAP), Computer Graphic Techniques, Computer Graphics, Computer Vision, Contract Management, Data Visualization, Geovisualization, Machine Learning, Operations Management, Planning, Supplier Relationship Management, Banking, Business Process Management, Financial Accounting, Financial Management, Inventory Management, Management Accounting, Business Communication, Forecasting, Journalism, Probability & Statistics
Crédito ofrecido
Graduate Certificate · 6-12 Months
University of Colorado Boulder
Data Science Graduate Certificate
Habilidades que obtendrás: Probability & Statistics, General Statistics, Regression, Data Analysis, Experiment, Statistical Analysis, Machine Learning, Business Analysis, Statistical Tests, Theoretical Computer Science, Probability Distribution, Machine Learning Algorithms, Data Management, Statistical Machine Learning, Mathematics, Data Mining, Deep Learning, Econometrics, Python Programming, Statistical Programming, Artificial Neural Networks, Applied Machine Learning, Data Warehousing, Correlation And Dependence, Algorithms, Reinforcement Learning, Calculus, Estimation, Exploratory Data Analysis, Basic Descriptive Statistics, Differential Equations, Feature Engineering, Natural Language Processing, Spreadsheet Software, Communication, Computer Programming, Data Science, Data Structures, Dimensionality Reduction, Linear Algebra, Marketing, R Programming, SQL
Crédito ofrecido
Graduate Certificate · 6-12 Months
University of Michigan
Python 3 Programming
Habilidades que obtendrás: Computer Programming, Python Programming, Computer Science, Statistical Programming, Algorithms, Other Programming Languages, Algebra, Communication, Computer Programming Tools, Journalism, Mathematics, Programming Principles, Software Engineering, Theoretical Computer Science
4.7
(20.3k reseñas)
Beginner · Specialization · 3-6 Months
IBM Skills Network
Scalable Machine Learning on Big Data using Apache Spark
Habilidades que obtendrás: Apache, Data Management, Big Data, Machine Learning, Probability & Statistics, Basic Descriptive Statistics, Business Analysis, Correlation And Dependence, Data Analysis, Databases, General Statistics, Machine Learning Algorithms, NoSQL, Regression, SQL, Statistical Analysis, Statistical Programming, Data Science
3.8
(1.2k reseñas)
Intermediate · Course · 1-4 Weeks

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

Master of Engineering in Engineering Management: University of Colorado Boulder
Engineering Management Graduate Certificate: University of Colorado Boulder
Data Science Graduate Certificate: University of Colorado Boulder
Semiconductor Photonics Graduate Certificate: University of Colorado Boulder
Python 3 Programming: University of Michigan
Scalable Machine Learning on Big Data using Apache Spark: IBM Skills Network
Applied Plotting, Charting & Data Representation in Python: University of Michigan
بايثون لعلوم البيانات والذكاء الصناعي: IBM Skills Network
Python para a Ciência de Dados e IA: IBM Skills Network
Python: обработка и анализ данных и ИИ: 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.