Advanced Analytics and 5G Systems Specialist
Course title: 5G O-RAN (Open RAN): Architecture, Procedures And Use Cases
Target group: Mid Level Employee
Level: Foundations
5G O-RAN (Open RAN): Architecture, Procedures And Use Cases
Provider
udemy
Description
O-RAN (or Open RAN) opens new avenues of service innovation and agility for telcos by breaking the Radio Access Network (RAN) into its component parts, each of which can be separately reconfigured. O-RAN standards are freely accessible to all third-party software developers, who can develop new types of services and innovate on the RAN Intelligent Controller (RIC) by building xApps and rApps. This enables telcos to make their networks a much more relevant resource for both enterprise and consumer applications.
Arguably the open RAN’s biggest claim is the potential to enable telcos to avoid vendor lock-in by replacing vendor-proprietary interfaces with a fully disaggregated RAN based on open standards.
Automation will be key to managing the lifecycle of disaggregated, cloud-native RAN functions. O-RAN can bring down the network deployment and operation cost by evolving the network in a continuous integration/ continuous delivery (CI/CD) manner rather than through generational investment cycles. This course covers all the important topics that are required to have a good and comprehensive learning of the O-RAN technology. The relevant standards of the O-RAN alliance have been discussed to describe the O-RAN architecture and working, as well as the O-RAN open interfaces.
Target
- Telecom engineers
- Network planners
- IT professionals in telecoms
- Network administrators
- Software developers in telecom
Sector
- Telecommunications
- Network Equipment vendors
- Telecom service providers
Area
- Radio Access Network (RAN)
- 5G network infrastructure
- Network automation
- Open standards implementation
Learning outcomes
- O-RAN (Open RAN) Concept in detail
- Evolution to O-RAN (vRAN, C-RAN, D-RAN, RAN Disaggregation)
- RAN Functional Split Options (specially option 7.2x)
- Enhanced CPRI (e-CPRI) Protocol
- O-RAN Architecture (SMO, Non RT RIC, Near RT RIC)
- Virtualization on O-RAN
- DEVOPS in O-RAN
- ORAN Use Cases (Traffic Steering, NSSI Optimization, UAV resource allocation)
Learning content
- Section 1: Introduction
- Section 2: Evolution to Open RAN
- Section 3: RAN Splits-Logical View
- Section 4: Overview of O-RAN Architecture
- Section 5: Virtualization techniques for O-RAN
- Section 6: Detailed O-RAN Architecture
- Section 7: O-RAN Traffic Steering Use Case
- Section 8: Network Slicing in 5G O-RAN
- Section 9: Other O-RAN Use Case
Approach/method
Online
Duration
3 hours on-demand video
Assessment
No
Certification
Yes
Cost
€54.99
Provider contacts
Date
Always available
Location
Online
Website
Course title: Machine Learning for All
Target group: Junior (Fresh Employee)
Level: Awareness
Machine Learning for All
Provider
Coursera
Description
Machine Learning, often called Artificial Intelligence or AI, is one of the most exciting areas of technology at the moment. We see daily news stories that herald new breakthroughs in facial recognition technology, self-driving cars or computers that can have a conversation just like a real person. Machine Learning technology is set to revolutionize almost any area of human life and work, and so will affect all our lives, and so you are likely to want to find out more about it. Machine Learning has a reputation for being one of the most complex areas of computer science, requiring advanced mathematics and engineering skills to understand it. While it is true that working as a Machine Learning engineer does involve a lot of mathematics and programming, we believe that anyone can understand the basic concepts of Machine Learning, and given the importance of this technology, everyone should. The big AI breakthroughs sound like science fiction, but they come down to a simple idea: the use of data to train statistical algorithms. In this course you will learn to understand the basic idea of machine learning, even if you don’t have any background in math or programming. Not only that, you will get hands on and use user friendly tools developed at Goldsmiths, University of London to actually do a machine learning project: training a computer to recognize images. This course is for a lot of different people. It could be a good first step into a technical career in Machine Learning, after all it is always better to start with the high-level concepts before the technical details, but it is also great if your role is non-technical. You might be a manager or other non-technical role in a company that is considering using Machine Learning. You really need to understand this technology, and this course is a great place to get that understanding. Or you might just be following the news reports about AI and interested in finding out more about the hottest new technology of the moment. Whoever you are, we are looking forward to guiding you through you first machine learning project. NB this course is designed to introduce you to Machine Learning without needing any programming. That means that we don’t cover the programming-based machine learning tools like python and TensorFlow.
Target
- Non-technical professionals (managers, executives) interested in understanding AI/ML
- Beginners without prior math or programming background
- Anyone interested in AI breakthroughs and technology trends
- Individuals considering a technical career in Machine Learning (as a first step)
Sector
- Business and Corporate Management
- Education and Academia
- Technology and Innovation (non-technical roles)
Area
- Artificial Intelligence / Machine Learning
- Data-driven decision making
- AI applications in image recognition and automation
Learning outcomes
- You will understand the basic of how modern machine learning technologies work
- You will be able to explain and predict how data affects the results of machine learning
- You will be able to use a non-programming based platform train a machine learning module using a dataset
- You will be able to form an informed opinion on the benefits and dangers of machine learning to society
Learning content
- Machine learning:
- In this topic you will learn about artificial intelligence and machine learning techniques. You will learn about the problems that these techniques address and will have practical experience of training a learning model.
- Data Features:
- In this topic you will learn about how data representation affects machine learning and how these representations, called features, can make learning easier.
- Machine Learning in Practice:
- In this topic you will get ready to do your own machine learning project. You will learn how to test a machine learning project to make sure it works as you want it to. You will also think about some of the opportunities and dangers of machine learning technology.
- Your Machine Learning Project:
- In this final topic you will do your own machine learning project: collecting a dataset, training a model and testing it.
Approach/method
Online
Duration
Approximately 20 hours
Assessment
Yes
Certification
Yes
Cost
Free
Provider contacts
Date
Always available
Location
Online
Website
Course title: Zero to Hero on Salesforce Data Cloud Training
Target group: Mid Level Employee
Level: Foundations
Zero to Hero on Salesforce Data Cloud Training
Provider
Udemy
Description
Master Salesforce Data Cloud with Confidence
Demystify Salesforce Data Cloud and take your career to the next level with our comprehensive online course.
Learn, Apply, and Advance Your Career Today
Are you a Salesforce professional looking to step into the future of data management? Our Salesforce Data Cloud Course on Udemy equips you with the skills and knowledge to implement Salesforce Data Cloud in real-world projects, unlocking new opportunities and career growth.
Whether you’re a Solution Architect, Technical Architect, or Salesforce Developer, this course is tailor-made to help you stand out in a competitive market by mastering Salesforce’s most cutting-edge platform.
Why Master Salesforce Data Cloud?
Salesforce Data Cloud is revolutionizing data management with unified customer profiles, real-time insights, and seamless integration across platforms. By mastering this platform, you’ll be equipped to solve critical business challenges and drive data-driven decisions effectively. Here’s why learners love this course:
- Hands-on Learning to Apply Immediately
Learn how to use tools like Data Cloud Modeling, Identity Resolution, and Segmentation through interactive, practical exercises you can apply to real-world scenarios.
- Boost Your Career Prospects
By mastering Data Cloud, you unlock job opportunities in high-demand roles across Salesforce ecosystems.
- Simplify Data Challenges
The course focuses on solving real-world data challenges, including managing Personally Identifiable Information (PII) and creating unified data profiles.
What You’ll Learn
Gain an in-depth understanding of Salesforce Data Cloud with topics that include:
- Building Unified Customer Profiles
Learn to consolidate customer data from multiple sources into a single, actionable view.
- Leveraging Data Modeling
Understand how to model and process data seamlessly for generating actionable insights.
- Working with Identity Resolutions
Explore advanced methods of matching and reconciling records for an accurate single source of truth.
- Mastering Data Transformations
Delve into both batch and streaming data transformation to empower real-time decision-making and historical analysis.
- Activating Data for Business Growth
Learn how to create audience segments and put insights to work in marketing campaigns or business strategies.
- Real-World Projects
Personalized training helps you build expertise through actionable insights and guided exercises from industry experts.
Target
- Salesforce Professionals (Solution Architects, Technical Architects, Developers)
- Data Management Specialists in Salesforce ecosystem
- Data Analysts and Business Intelligence professionals
Sector
- Technology / Software / Cloud Computing
- Information Technology / Data Management
- Salesforce and Cloud CRM solutions
Area
- Data Management and Integration
- Customer Data Platform (CDP) / Data Cloud
- Real-time Data Processing and Insights
- Customer Relationship Management (CRM) Data Enhancement
Learning outcomes
- Master core capabilities like DLO, DSO, and DMO to optimize Salesforce Data Cloud operations.
- Learn to ingest and process data from AWS S3 Server for seamless integration and transformation.
- Gain skills in identity resolution, segmentation, and activation to enhance personalized customer experiences.
- Apply knowledge through real-world projects to build practical expertise in Salesforce Data Cloud.
Learning content
- Foundations Of Salesforce Data Cloud
- Core Capabilities of Data Cloud
- Data Ingestion and Storage
- Data Modeling and Mapping
- Data Transform and Data Space
- Identity Resolution
- Data Cloud Insights Using AWS Data Set
- Segmentation and Activation
- Real Time Project – Customer Purchase Behavior Analysis
Approach/method
Online
Duration
10.5 hours on-demand video
Assessment
No
Certification
Yes
Cost
€54.99
Provider contacts
Date
Always available
Location
Online
Website