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In this course, you will :
- Learn about the history of data science and its subfields, their roles in the market, and the five main skills you'll need to succeed: data mining, machine learning, natural language processing, statistics, and visualisation.
- Discover potential roles, career options, ethics, and professional development.
- Also, learn about the leading industry-recognized certifications that can help you stand out in your field.
- Jungwoo collects testimony and shares real-world insights from data science professionals at various stages of their careers along the way.
Syllabus :
1. Defining Data Science
- Fundamentals
- Big data analytics
- Enabling technologies
2. Marketplaces
- Fraud detection
- Social media analytics
- Disease control
- Dating services
- Simulations
- Climate research
- Network security
3. Skills
- Required skills
- Data mining and analytics
- Machine learning
- Natural language processing
- Statistics
- Visualization
4. Roles
- Data scientist or engineer
- Business intelligence architect
- Machine learning scientist
- Business analytics specialist
- Data visualization developer
- Salaries
5. Certifications
- Azure Data Scientist Associate certification
- Cloudera Data Platform certification
- EMC Data Science Associate
- AWS and Google certification
- SAS big data and data scientist certifications
- Certified Analytics Professional (CAP)
6. Future of Data Science
- Emerging technologies
- Emerging careers
- Ethics
- Professional development
7. Voices from the Field
- Senior data scientist
- College senior
- Graduate student
- Employer
- How to start
