English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 12m | 200 MB
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, this course is for you.
Jungwoo Ryoo is a professor of information science and technology at Penn State. Here he reviews the history of data science and its subfields, explores the marketplaces for these fields, and reveals the five main skills areas: data mining, machine learning, natural language processing (NLP), statistics, and visualization. This leads to a discussion of the five biggest career opportunities, the six leading industry-recognized certifications available, and the most exciting emerging technologies. Along the way, Jungwoo discusses the importance of ethics and professional development, and provides pointers to online resources for learning more.
Topics include:
- A history of data science
- Why data analytics is important
- How data science is used in fraud detection, disease control, network security, and other fields
- Data science skills
- Data science roles
- Data science certifications
- The future of data science
Table of Contents
Introduction
1 Welcome
2 What you should know before watching this course
Define Data Science
3 Introduction
4 A brief history
5 Fundamentals
6 Big data analytics
7 Enabling technologies
Marketplace
8 Introduction to marketplace
9 Fraud detection
10 Social media analytics
11 Disease control
12 Dating services
13 Simulations
14 Climate research
15 Network security
Skills
16 Required skills
17 Data mining and analytics
18 Machine learning
19 Natural language processing (NLP)
20 Statistics
21 Visualization
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
Certifications
29 Introduction to certifications
30 MCSE Business Intelligence
31 Cloudera Certified Professional (CCP) Data Scientist
32 EMC Data Science Associate (EMCDSA)
33 Oracle Business Intelligence certificate
34 SAS Certified Big Data Professional and Certified Data Scientist
35 Certified Analytics Professional
Future of Data Science
36 Introduction to the future of data science
37 Emerging technologies
38 Emerging careers
39 Ethics
40 Professional development
Conclusion
41 Next steps and additional resources
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