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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Applied Data Science

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519 resultados para "applied data science"

Gratis
The Hong Kong University of Science and Technology
Python and Statistics for Financial Analysis
Habilidades que obtendrás: Business Analysis, Computer Programming, Data Analysis, Financial Analysis, Python Programming, Statistical Programming, Finance, Investment Management, Probability & Statistics, Probability Distribution, Statistical Analysis, Basic Descriptive Statistics, Correlation And Dependence, General Statistics, Regression, Risk Management, Securities Trading, Statistical Tests, Accounting, Estimation
4.4
(3.7k reseñas)
Intermediate · Course · 1-4 Weeks
IBM Skills Network
Data Visualization with R
Habilidades que obtendrás: Data Visualization, Data Visualization Software, R Programming, Interactive Data Visualization, Plot (Graphics), Data Analysis, Data Analysis Software, Exploratory Data Analysis, Software Visualization, Basic Descriptive Statistics, Statistical Visualization, User Experience, Statistical Analysis, Visualization (Computer Graphics), Data Science, Statistical Programming
4.6
(144 reseñas)
Beginner · Course · 1-4 Weeks
Microsoft
Azure Data Lake Storage Gen2 and Data Streaming Solution
Habilidades que obtendrás: Big Data, Computer Architecture, Computer Networking, Data Analysis, Data Management, Network Architecture, Accounting, Business Analysis, Cloud Computing, Financial Analysis, Cloud Storage, Microsoft Azure, Business Psychology, Entrepreneurship, Leadership and Management, Organizational Development
4.1
(20 reseñas)
Intermediate · Course · 1-4 Weeks
Macquarie University
Influencing: Storytelling, Change Management and Governance
Habilidades que obtendrás: Leadership and Management, Communication, Strategy and Operations, Marketing, Entrepreneurship, Negotiation, Sales, Change Management, Risk Management, Business Psychology, Conflict Management, Influencing, Human Resources, Organizational Development, Business Communication, Business Process Management, Culture, Business Analysis, Critical Thinking, Data Analysis, Decision Making, Emotional Intelligence, Leadership Development, Probability & Statistics, Research and Design, Statistical Tests, Storytelling
4.8
(3.2k reseñas)
Beginner · Specialization · 3-6 Months
Google
Fundamentos de la gestión de proyectos
Habilidades que obtendrás: Entrepreneurship, Leadership and Management, Project Management, Strategy and Operations, Supply Chain and Logistics, Planning, Business Psychology, Communication, Marketing, Organizational Development, Agile Software Development, Change Management, Culture, Emotional Intelligence, Negotiation, Operations Management, Sales, Scrum (Software Development), Software Engineering, Software Engineering Tools
4.9
(3k reseñas)
Beginner · Course · 1-4 Weeks
Gratis
Meta
Advanced Programming in Swift
Habilidades que obtendrás: Mobile Development, Swift Programming, iOS Development, Computer Programming, Data Management, Data Structures, Software Engineering, Theoretical Computer Science, Programming Principles, Algorithms, Communication, Computer Programming Tools, Software Testing, Application Development, Journalism
4.8
(26 reseñas)
Intermediate · Course · 1-4 Weeks

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

Python and Statistics for Financial Analysis: The Hong Kong University of Science and Technology
Data Visualization with R: IBM Skills Network
Creating an Interactive Graph with Tableau Public: Coursera Project Network
Sourcing Analytics: Rutgers the State University of New Jersey
Azure Data Lake Storage Gen2 and Data Streaming Solution: Microsoft
Science of Training Young Athletes Part 2: University of Florida
Influencing: Storytelling, Change Management and Governance: Macquarie University
Fundamentos de la gestión de proyectos: Google
Social Pedagogy across Europe: Universitat Autònoma de Barcelona
Cryptography: (ISC)²

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.