English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 32m | 860 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, 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.
Table of Contents
Introduction
1 An expanding universe of data science career options
2 What you should know
Defining Data Science
3 Introduction
4 A brief history
5 Fundamentals
6 Big data analytics
7 Enabling technologies
Marketplaces
8 Introduction to marketplaces
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
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 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)
Future of Data Science
36 Introduction to the future of data science
37 Emerging technologies
38 Emerging careers
39 Ethics
40 Professional development
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
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