Data Science and Analytics Career Paths and Certifications: First Steps
1h 32mBeginner2022-02-10
Authors
Jungwoo Ryoo
Teaches IT, cybersecurity, and risk analysis at Penn State
Course details
The career opportunities in data science, big data, and data analytics are growing dramatically. If you're interested in changing career paths, determining the right course of study, or deciding if certification is worth your time, check out this course with information science and technology professor Jungwoo Ryoo.
Explore the history of data science and its subfields, their roles in the marketplace, and the five main skills that you need to know to succeed: data mining, machine learning, natural language processing, statistics, and visualization. Learn about potential roles, career opportunities, ethics, and professional development. And get tips on the leading industry-recognized certifications that can set you apart in the field. Along the way, Jungwoo gathers testimony and shares real-world insights from data science professionals at various stages in their careers.
Explore the history of data science and its subfields, their roles in the marketplace, and the five main skills that you need to know to succeed: data mining, machine learning, natural language processing, statistics, and visualization. Learn about potential roles, career opportunities, ethics, and professional development. And get tips on the leading industry-recognized certifications that can set you apart in the field. Along the way, Jungwoo gathers testimony and shares real-world insights from data science professionals at various stages in their careers.
Skills covered
First StepsData Science FoundationsTech Career SkillsCareer ManagementCareer DevelopmentData AnalysisCybersecurityCloud ComputingData ScienceBusiness Analysis and StrategyBusiness Software and ToolsSoftware Development
Concepts
0. Introduction
- 01 - An expanding universe of data science career options
- 02 - What you should know
1. Defining Data Science
- 03 - Introduction
- 04 - A brief history
- 05 - Fundamentals
- 06 - Big data analytics
- 07 - Enabling technologies
2. Marketplaces
- 08 - Introduction to marketplaces
- 09 - Fraud detection
- 10 - Social media analytics
- 11 - Disease control
- 12 - Dating services
- 13 - Simulations
- 14 - Climate research
- 15 - Network security
3. Skills
- 16 - Required skills
- 17 - Data mining and analytics
- 18 - Machine learning
- 19 - Natural language processing
- 20 - Statistics
- 21 - Visualization
4. Roles
- 22 - Introduction to roles
- 23 - Data scientist or engineer
- 24 - Business intelligence architect
- 25 - Machine learning scientist
- 26 - Business analytics specialist
- 27 - Data visualization developer
- 28 - Salaries
5. Certifications
- 29 - Introduction to certifications
- 30 - Azure Data Scientist Associate certification
- 31 - Cloudera Data Platform certification
- 32 - EMC Data Science Associate
- 33 - AWS and Google certification
- 34 - SAS big data and data scientist certifications
- 35 - Certified Analytics Professional (CAP)
6. Future of Data Science
- 36 - Introduction to the future of data science
- 37 - Emerging technologies
- 38 - Emerging careers
- 39 - Ethics
- 40 - Professional development
7. Voices from the Field
- 41 - Introduction to voices from the field
- 42 - Senior data scientist
- 43 - College senior
- 44 - Graduate student
- 45 - Employer
- 46 - How to start
Conclusion
- 47 - Continue your data science and analytics career journey