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Artificial Intelligence and Machine Learning, Azure, Cloud Computing
6 Mins Read
Do you have an aspiration of becoming a Data Scientist? If yes, then you must be checking out lots of material over the internet to find the best path. As we know Data Science and Artificial Intelligence (AI) is a classic mix of computer science, coding and statistics. To prove that you are one of the best in this field, there are few certification exams available that you can clear. This blog article is dedicated to one of the Machine Learning (ML) exams from Microsoft which clearly states the suitable audience as Data Scientists.
With this article I am going to help you understand the vital aspects of this exam. Also, if you are keen to appear and enjoy the recognition to be the few people on the planet to clear it quite early like me, then this article is for you.
70-774 is a dedicated exam which focuses on skills to develop and consume Machine Learning models using Azure Machine Learning Service and Azure Cognitive Services on public Cloud of Microsoft Azure. There are four major objectives including expectations of this exam explained in this blog article. The exam contains case study based and stand-alone questions. The number of questions could be anywhere around 40 (I got 37!). It’s a typical Microsoft exam allowing candidates to finish exam in 150 minutes. I can say that one can learn every topic of this exam, but three things are highly recommended before starting:
First: Statistics 101 knowledge which is required to fully understand the AI methods and algorithms.
Second: Basic Python or R knowledge.
Third: Understanding of few Azure Cloud Services and its functions not all, but including – Azure Storage Account, Azure Data Factory, Azure HDInsight, Azure Cognitive Services, Azure VM and Azure SQL.
So, if you have not used Azure at any point of time, please get your free trial account and start exploring. You can visit here Cloud Computing with Microsoft Azure – Level 2 to find out one of the best ways to jump start learning Azure. For Data Scientists, this exam is all about optimally utilizing Azure ML platform for operations, but for newbies it’s much more than this. I feel it is an opportunity to learn a lot of important Data Science concepts for building stronger base in Machine Learning technologies.
The focus area of this objective is to find out how good a candidate possess knowledge about the data pre-processing which is a vital process done by every Data Scientist before developing a perfectly working Machine Learning model. If you are new to Data Science, then go ahead and understand the importance of following topics:
Well I can say that all these requires major effort and takes good amount of time without the right guidance. If you want to cut down your time and effort, you can gain all this knowledge here Machine Learning Essentials – Level 2 from experienced professionals.
If you are aware about the Azure Machine Learning environment, you would know that there are many modules which are used in building up a ML model. These modules are pre-configured and packaged piece of codes which performs a certain function. As far as this objective is concerned, there will be questions around the following modules:
It is highly recommended that you follow the Microsoft Azure documentation and perform labs related to all modules which I am mentioning not only in this objective, but also for the entire article. It is important to understand when to use a module, what properties of a module needs to be configured, what is the expected outcome and in the entire flow of a Machine Learning model which places this module can fit in.
In this objective, the candidate needs to prove his skills in selecting and configuring the right algorithm suitable for various real-life scenarios. Before you kick start your learning process, you need to make sure that you go through these topics if you are new to Data Science:
The questions in this section would be around the following modules:
There are 25 algorithms which you need to understand as supported natively by Azure ML. A couple of questions in the exam would demand you to know which algorithm should be used as per the scenario. For this, you can download this cheat sheet for your reference.
Also, don’t forget to learn the evaluation metrics for all types of algorithms including classification, regression, clustering and recommendation. These metrics would need you to have some basics of statistics as they are purely mathematical values. These metrics helps you understand how well the model is designed.
This objective focuses on one’s operational capability with Microsoft Azure ML platform. There are couple of tasks which needs to be done as a process to create, publish and utilize the Machine Learning models. A practical hands-on with Azure Machine Learning is the best approach to prepare for this objective.
Having an Azure subscription is vital for this. Refer Azure documentation to create an end to end sample Machine Learning model. Gather some information related to Jupyter notebooks if you have never worked with a notebook software. Microsoft Azure natively supports Jupyter notebooks. Notebook software are quiet famous in Data Science as they allow developers to create and share models easily.
Learn how to connect to the web service of Machine Learning models for consumption. Understand the differences and advantages between consuming the Machine Learning models using batch execution vs request response.
Apart from the Azure Machine Learning Service, Microsoft also provides Cognitive Services which helps to implement AI functionalities in smart solutions on the go. These cognitive services are hosted on Cloud and it can be accessed via APIs. There are three cognitive services under the scope of this certification exam: Computer Vision, Language and Knowledge.
Computer Vision APIs are useful in performing face detection, face recognition, OCR and object detection. Language APIs are useful in processing text. It is capable enough to understand more than 120 languages and they are widely used for processes like sentimental analysis. Knowledge APIs are the one which provides knowledge from a defined source and helps create recommendations. Learn about their functionalities and try few API calls with these cognitive services to practice better.
Microsoft have launched an open source deep learning toolkit called CNTK or Cognitive Toolkit. This can be installed on any machine whether local or Cloud. Unlike a PaaS service like Azure Machine Learning, CNTK provides a platform which inclines towards IaaS. With the enhancement of GPU based technology used for Data Science processing, NVIDIA has specially launched N-series machines on Azure and similar offerings on other Clouds. I have seen that for examination you don’t have to be proficient in using CNTK, but little bit of hands-on could give you an advantage. Just go through the documentation and few tutorials as shown here. The process of creating Feed Forward Neural Network is defined in the documentation.
Cortana Intelligence Gallery has a lot of ready to use templates which turns on certain Azure services in the right configuration needed for various projects. It is very simple to start an experiment using a template from this gallery. Login to the gallery, choose your template and just jumpstart. Go through the process once to checkout all details as it would be helpful for the exam.
Azure HDInsight is a deep subject as it is a wide service. From exam perspective, you can go ahead and learn the types of clusters, their default configurations and use cases. Though exam objectives states that working with Spark HDI and Spark SQL is vital, I don’t see any reason for a disappointment if you don’t know Spark as it doesn’t seem a heavily dependent topic.
For data analysis with SQL Server, there are three things that you should know for the exam:
It is always great to get the right source of learning to Move Up. At CloudThat we have a course aimed at preparing participants for 70-774 Certification Exam i.e. Perform Cloud Data Science with Azure Machine Learning: 70-774 BootCamp
Feel free to drop any questions in the comment box, I would love to address them. I hope you enjoyed the article. Best of luck!
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AI/ML, AWS, Cloud Computing
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Cloud Computing, Cyber Security, DevOps
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Aug 2, 2022
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Aug 1, 2022
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Aug 1, 2022
Case Study
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Jul 25, 2022
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AWS, Cloud Computing
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AWS, Cloud Computing
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AWS, Cloud Computing
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Jul 20, 2022
Cloud Computing
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Jul 18, 2022
Cloud Computing
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Jul 15, 2022
Cloud Computing, Industry Stories
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Cloud Computing, Industry Stories
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AWS, Cloud Computing
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AWS, Cloud Computing
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Cloud Computing
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AWS, Cloud Computing, Cyber Security
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Azure, Cloud Computing
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AI/ML, AWS, Cloud Computing
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AI, AWS, Cloud Computing
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Azure, Cloud Computing
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AWS, Cloud Computing
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AWS, Cloud Computing
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AWS, Cloud Computing
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Cloud Computing, Cloud security, Cyber Security
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AWS, Cloud Computing
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AWS, Cloud Computing
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Cloud Computing, DevOps
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AWS, Cloud Computing, Data Analytics
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Azure, Cloud Computing
By Rahul Kumar Sharma
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Cloud Computing, DevOps
By Ullas Vardhan Chaturvedi
Jun 8, 2022
Cloud Computing, Data Analytics
By Sai Pratheek
Jun 8, 2022
Azure, Cloud Computing
By Saritha Nagaraju
Jun 6, 2022
AWS, Cloud Computing
By Guru Bhajan Singh
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AWS, Cloud Computing
By Akshay Mishra
Jun 6, 2022
AWS, Cloud Computing
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AWS, Cloud Computing, Cyber Security
By Anil Reddy
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Cloud Computing, Cloud Native Application Development
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AWS, Cloud Computing, Kubernetes
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Cloud Computing, Cloud security, Cyber Security
By Rajesh KVN
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Cloud Computing, Cloud Native Application Development
By Rahul Kumar Jha
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Azure, Cloud Computing, Containerization
By Anees A
May 20, 2022
Azure, Cloud Computing
By Ismayil Siyad
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Cloud Computing, DevOps
By Kavyashree K
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AWS, Cloud Computing, DevOps
By Prarthit Mehta
May 16, 2022
AWS, Cloud Computing
By Nidhin Manjaly
May 16, 2022
AWS, Cloud Computing
By Karthik Kumar P V
May 16, 2022
AWS, AWS Amplify, Cloud Computing
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May 16, 2022
Azure, Cloud Computing
By Mayank Bharawa
May 13, 2022
AWS, Cloud Computing
By Sanket Gaikwad
May 13, 2022
AWS, Azure, Cloud Computing
By Prarthit Mehta
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Azure, Cloud Computing, Power Platforms
By Ravichandra M
May 10, 2022
AI/ML, AWS, Cloud Computing
By Vasanth Kumar R
May 9, 2022
Azure, Cloud Computing, DevOps
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May 9, 2022
Cloud Computing, Cyber Security
By Shivani Gandhi
May 9, 2022
AWS, Cloud Computing
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May 9, 2022
Cloud Computing, Google Cloud (GCP)
By Shaik Munwar Basha
May 9, 2022
AI/ML, Cloud Computing
By Anusha Shanbhag
May 9, 2022
Azure, Cloud Computing, Microsoft 365
By Rajesh KVN
May 6, 2022
AWS, Cloud Computing
By Mahek Tamboli
May 5, 2022
Azure
By Vishal Kalwapalli
May 4, 2022
Cloud Computing, Cloud security, Cyber Security
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May 3, 2022
Cloud Computing, Power Platforms
By Raji P
May 2, 2022
AI/ML, AWS, Cloud Computing
By Vasanth Kumar R
May 2, 2022
Azure, Cloud Computing
By Vishal Kalwapalli
May 2, 2022
Cloud Computing
By Ravichandra M
May 1, 2022
Cloud Computing
By Rajesh KVN
May 1, 2022
AWS, Cloud Computing
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Apr 27, 2022
AWS, Cloud Computing
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Apr 26, 2022
Azure, Cloud Computing
By Daneshwari Mathapati
Apr 26, 2022
AWS, Cloud Computing
By Rishi Raj
Apr 22, 2022
AWS, Cloud Computing
By Rahul Kumar Sharma
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AWS, Cloud Computing
By Guru Bhajan Singh
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AI/ML, AWS, Cloud Computing
By Rishi Raj
Apr 21, 2022
AWS, Cloud Computing
By Suresh Kumar Reddy
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AWS, Azure, Cloud Computing
By Sridhar Immanni
Apr 18, 2022
AWS, Cloud Computing
By Rahul Kumar Sharma
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AI/ML, AWS, Cloud Computing
By Shaik Munwar Basha
Apr 18, 2022
AWS, Cloud Computing
By Aishwarya Joshi
Apr 16, 2022
Azure, Cloud Computing
By Rekha S
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AWS, Cloud Computing
By Prarthit Mehta
Apr 11, 2022
AI/ML, AWS
By Bineet Singh Kushwah
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AWS, Cloud Computing
By Sonam Kumari
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Cloud Computing
By Ravichandra M
Apr 7, 2022
AWS, Cloud security, Microsoft Azure
By Kavyashree K
Apr 6, 2022
AWS, Cloud Computing
By Cherukula Bhanu Prakash Reddy
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DevOps, Docker
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Apr 5, 2022
Cloud Computing
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Apr 3, 2022
Cloud Computing
By Ananya Pandey
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AWS, Cloud Computing
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AI/ML, AWS, Cloud Computing
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AWS, Cloud Computing
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Cloud Computing
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AWS, Cloud Computing
By Guru Bhajan Singh
Mar 22, 2022
Cloud Computing
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AWS, Cloud Computing
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Mar 22, 2022
AI/ML, Azure, Azure Machine Learning
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Mar 21, 2022
Cloud Computing
By Akshay Mishra
Mar 20, 2022
AWS, Cloud Computing
By Aishwarya Joshi
Mar 20, 2022
Cloud Computing, Cloud Data Science
By Bineet Singh Kushwah
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By Ravichandra M
Mar 16, 2022
AWS, Cloud Computing
By Rishi Raj
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Azure, Cloud Computing
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AWS, Cloud Computing
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AWS, Azure, Cloud Computing
By Ravichandra M
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Feb 13, 2022
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AWS, Cloud Computing
By Prarthit Mehta
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AWS, Cloud Computing
By Vasanth Kumar R
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Azure, Cloud Computing
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AWS, Cloud Computing
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AWS, Cloud Computing
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Cloud Computing
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Jan 21, 2022
AWS, Cloud Computing
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AWS, Cloud Computing
By Sai Pratheek
Jan 13, 2022
AWS, Cloud Computing
By Anil Reddy
Jan 13, 2022
Azure, Cloud Computing
By Vishal Kalwapalli
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Apps Development, Azure, Cloud Computing
By Ananya Pandey
Jan 5, 2022
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Jan 4, 2022
AWS, Cloud Computing, Data Analytics
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Jan 4, 2022
AWS, Cloud Computing, DevOps
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Jan 4, 2022
AWS, AWS PinPoint, Cloud Computing
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Jan 3, 2022
Azure, Cloud Computing
By Rajesh KVN
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AWS, Cloud Computing
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Azure, Cloud Computing, Cloud Data Science
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AWS, Cloud Computing, DevOps
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AWS, Cloud Computing
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AWS, Cloud Computing
By Prarthit Mehta
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Cloud Computing, Cloud Migration
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Dec 20, 2021
AWS, Cloud Computing
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Dec 20, 2021
Automation, AWS, Cloud Computing
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Cloud Computing
By Ravichandra M
Dec 14, 2021
Azure, Cloud Computing
By Ravichandra M
Dec 9, 2021
AI/ML, Artificial Intelligence, AWS
By Ravichandra M
Dec 6, 2021
Cloud Computing
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Dec 1, 2021
Cloud Computing
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Dec 1, 2021
Cloud Computing, Cyber Security, Identity Access and Management
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Azure, Cloud Computing
By Sai Pratheek
Nov 18, 2021
Cloud Computing, Microsoft Azure
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Project Management
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AWS, Cloud Computing
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Analytics, Azure, Big Data
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Apps Development, Certification BootCamp, Cloud Computing
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By Anusha Shanbhag
Jun 30, 2021
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By Sridhar Immanni
Jun 15, 2021
AWS, Cloud Computing
By Rekha S
Jun 13, 2021
Analytics, Azure, Azure Machine Learning
By Gurjot Brar
Jun 2, 2021
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By Anusha Shanbhag
May 31, 2021
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By Shyla J
May 21, 2021
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By Sindhu Priya M
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By Shabana R
May 17, 2021
Azure, Cyber Security, Microsoft Azure
By CloudThat
May 10, 2021
AWS, Azure, Cloud Computing
By Prarthit Mehta
May 10, 2021
Azure, Cloud Computing
By Shaik Munwar Basha
May 8, 2021
AI/ML, Artificial Intelligence, Azure
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May 7, 2021
AWS, Azure, Google Cloud (GCP)
By Daneshwari Mathapati
Apr 29, 2021
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Apr 26, 2021
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By Anusha Shanbhag
Apr 26, 2021
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Cloud Computing, Data Analytics
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Apr 15, 2021
AWS, Azure, Cloud Computing
By Daneshwari Mathapati
Apr 5, 2021
Cloud Computing, Cyber Security
By CloudThat
Mar 30, 2021
Azure, Cloud Computing
By CloudThat
Mar 30, 2021
Azure, Cloud Computing
By CloudThat
Mar 24, 2021
Azure, Cloud Computing
By Anusha Shanbhag
Mar 12, 2021
Azure, Cloud Computing
By Shaik Munwar Basha
Mar 11, 2021
Azure, Cloud Computing
By Anusha Shanbhag
Mar 1, 2021
Azure, Cloud Computing
By Anusha Shanbhag
Feb 25, 2021
Kevin
Aug 31, 2018
Any idea what percentage you need to get to pass the exam?
And it would be awesome if you could post a few sample questions so that we could get an idea of the format/what to expect, etc.
Thanks!!
simran
Mar 29, 2018
thanks for the post..was very useful
Varsha Kulkarni
Mar 29, 2018
Very useful ! Thank you
rsat
Mar 16, 2018
Thank you, Tiia! I hope you try them soon!