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IGTC01DA - Data Science & Analytics Career Paths & Certifications First Steps (EN)
01 - Introduction
01 - Welcome (1:09)
02 - What you should know before watching this course (0:47)
02 - 1. Define Data Science
01 - Introduction (1:24)
02 - A brief history (2:37)
03 - Fundamentals (3:15)
04 - Big data analytics (1:44)
05 - Enabling technologies (2:51)
03 - 2. Marketplace
02 - Fraud detection (2:05)
01 - Introduction to marketplace (1:26)
03 - Social media analytics (2:09)
04 - Disease control (1:24)
05 - Dating services (1:51)
06 - Simulations (1:28)
07 - Climate research (1:24)
08 - Network security (1:16)
04 - 3. Skills
01 - Required skills (2:42)
02 - Data mining and analytics (1:50)
03 - Machine learning (1:33)
04 - Natural language processing (NLP) (1:58)
05 - Statistics (1:11)
06 - Visualization (1:35)
05 - 4. Roles
02 - Data scientist or engineer (1:48)
01 - Introduction to roles (1:49)
03 - Business intelligence architect (1:33)
04 - Machine learning scientist (3:01)
05 - Business analytics specialist (1:48)
06 - Data visualization developer (2:26)
07 - Salaries (1:32)
06 - 5. Certifications
01 - Introduction to certifications (3:06)
02 - MCSE Business Intelligence (0:48)
03 - Cloudera Certified Professional (CCP) Data Scientist (1:17)
04 - EMC Data Science Associate (EMCDSA) (0:56)
05 - Oracle Business Intelligence certificate (1:17)
06 - SAS Certified Big Data Professional and Certified Data Scientist (1:58)
07 - Certified Analytics Professional (2:30)
07 - 6. Future of Data Science
02 - Emerging technologies (1:44)
01 - Introduction to the future of data science (1:50)
03 - Emerging careers (1:34)
04 - Ethics (1:51)
05 - Professional development (1:45)
08 - Conclusion
01 - Next steps and additional resources (0:28)
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01 - Introduction to certifications
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