Internet of Things and the Cloud

Accrediations

University of California

Durartion of the Course

24 Weeks

Course Fee

$140

Mode of Learning

Self-Paced

What is The Course All About?

The Internet of Things and AI Cloud Specialization Course provided by Allison is an online Computer science course made to build one’s expertise in Computer Science.

Who is the Course Meant For?

Being an intermediate-level course, the Internet of Things and AI Cloud Specialization Course is an ideal course for learners like:

A fresher who wants to build their career in Computer Science,
IT professionals who want to upskill themselves in Computer Science,
Any individuals who want to learn Computer Science or build their carer in the same.

Accreditations and Rankings

What are the Certificates and Accreditations of this Course

Skills: What does this program cover?

Depth and Breadth of Topics
ⓘ
- Range of topics covered. - Number of topics, comprehensiveness (introductory to advanced)
- Theoretical vs. practical balance
- Alignment with industry standards and current trends
Strong
Case Studies
ⓘ
- Number and variety of case studies
- Relevance of case studies to the course topic and target audience
Strong
Tools
ⓘ
- Use of industrystandard tools and technologies
- Handson experience with tools
Strong
Capstone Projects/Real World Application
ⓘ
- Presence of a project or practical application
- Complexity and scope of the project
Strong

Skills: 30 /30

Faculties: Who are the experts behind the course?

Academic/Industry Exp.
ⓘ
- Educational background
- Work experience in relevant industries
Strong
Teaching Experience
ⓘ
- Experience teaching similar courses or topics
- Teaching style and approach (engaging, clear, accessible)
Strong
Industry Recognition
ⓘ
- Awards and recognition in the field
- Contributions to opensource projects, communities, or publications
Strong

Faculties: 20 /20

Delivery Methods: How Is the program delivered?

Live Interaction
ⓘ
- Availability of live lectures, Q&A sessions, or webinars
- Provide direct interaction and realtime clarification of concepts
- Quality and effectiveness of live interactions
Strong
Self-Paced
ⓘ
- Flexibility in scheduling and pacing
- Prerecorded videos covering lectures, tutorials, demonstrations, and supplemental content, allowing students to engage with course material flexibly.
- Quality and availability of selfpaced materials (videos, readings, exercises)
Strong
Assessment
ⓘ
- Variety of assessment types (quizzes, assignments, projects)
- Alignment of assessments with learning objectives
- Quality and timeliness of feedback on assessments
Strong
Community
ⓘ
- Presence and activity of online forums, discussion boards, or other community spaces
- Level of engagement and support from instructors and moderators
Strong
Collaborative
ⓘ
- Opportunities for group projects, peer review, or other collaborative activities
Strong

Delivery Methods: 30 /30

Career Assistance: How does the program support career growth?

Mentoring
ⓘ
- Availability of personalized guidance and support from mentors or career coaches
Strong
Personalized Assistance
ⓘ
- Availability of career Assessments (personality, skills, interests) to help learners understand their strengths and potential career paths
Strong
Alumni Network
ⓘ
- Active alumni network for networking
Strong
Industry Partnerships
ⓘ
- Partnerships with companies
Strong

Career Assistance: 15 /15

Student Satisfaction and Feedback: What Do Students Say About the Course?

Feedback & Improvement
ⓘ
- Quantity and quality of student reviews
- Responsiveness of course providers to feedback
- Evidence of continuous improvement in the course content and delivery
Strong

Alumini Feedback: 5 /5

Benchmark Labels:

Strong (75-100%): This indicates the course demonstrates exceptional strengths in this area, exceeding expectations.

Moderate (50-74%): This signifies the course performs adequately in this area, covering essential aspects.

Limited (25-49%): This highlights areas where the course could significantly improve to provide a more comprehensive learning experience.

Very Limited (1-24%): This indicates that coverage in this area may be minimal, or even non-existent.

Not Applicable: This indicates that this criteria is not applicable for this course.