Given the high demand for cloud professionals, an increasing number of candidates are choosing cloud computing as their preferred career path. This surge in interest has led to a proliferation of courses in the market, each claiming to provide the necessary skills and knowledge. However, not all of these courses are created equal. To make an informed decision and select a program that will truly serve their career goals, aspiring cloud professionals must not only consider course providers but also delve into the intricacies of the cloud computing syllabus. Understanding the core topics and competencies covered in these courses is essential for aspiring cloud experts to chart a successful career path in this dynamic and in-demand field.
Cloud Computing Course Overview
The cloud computing syllabus aims to provide students with a comprehensive insight into the world of cloud computing. Starting from applications, programming, and administration, it ranges to large-scale distribution systems, which comprise the cloud computing infrastructure.
Furthermore, via hands-on projects, applicants learn the ways to utilize public cloud computing platforms like Microsoft Azure and Amazon Web Services (AWS).
Benefits of Cloud Computing Certification
Here are some of the benefits you can get by opting for cloud computing certification:
1. Increases Your Earnings Potential
As per reports by Glassdoor India, cloud engineers have an average salary of ₹6.82 lakh per annum. Additionally, in the USA, individuals can earn approximately $122,943 per annum in this job role.
Apart from this, with an AWS Cloud Certification, the standard yearly package in India ranges around ₹5 lakh per annum, while an Azure Cloud Certification can fetch around ₹6 lakh per annum.
Therefore, learning cloud computing can serve as a gateway for a high-paying career.
2. Adds Weight to Your Resume
Having a cloud certification acts as proof to the recruiter that you have the necessary skills to perform your job role as a cloud professional. Moreover, most multinational companies require cloud certifications as a basic criterion when recruiting candidates.
Hence, including such certificates in your resume enhances your chances of getting hired by a prospective employer.
3. Gives a Significant Boost to Your Career
As most companies are adopting cloud infrastructure, there will be a high demand for cloud professionals in the long run. So, individuals with computer science or an IT background can get a massive career boost by choosing this path.
Cloud Computing Course Syllabus
Find the cloud computing course syllabus mentioned in the table below:
Unit | Title | Description |
1 | Introduction to Cloud Computing | This module introduces learners to the world of cloud computing. It discusses the definition of cloud computing, its evolution, pros, cons, and challenges. Additionally, students learn about service and deployment models, SLAs, economic models, cloud security, enabling technologies, popular cloud stacks, and their use cases. |
2 | What is Cloud Infrastructure | Candidates gain insight into the history of data centers, their components like IT equipment and facilities, along with design considerations like efficiency, power, requirements, redundancy, and more. |
3 | Cloud Storage | This unit covers cloud storage systems, their concepts, object storage (Ceph, OpenStack Swift, and Amazon S3), databases (DynamoDB, HBase, Cassandra, and MongoDB), and distributed file systems (Ceph FS and HDFS). |
4 | Virtualization (with Case Studies) | In this unit, students learn about virtualization and its components (memory, CPU, I/O). It also discusses case studies on Software Defined Storage (SDS), Software Defined Networks (SDN), and Amazon EC2. |
5 | Programming Models | Students study data-parallel analytics along with Hadoop MapReduce (YARN), distributed programming for the cloud, graph parallel analytics (with GraphLab 2.0), and iterative data-parallel analytics (with Apache Spark). |
Cloud Computing Course Projects
The projects included in the Cloud Computing Syllabus are as follows:
Project 1 – Working With AWS
As the name suggests, in this project, students get first-hand experience working with AWS. They set up their accounts, learn the ins and outs of the management software, and launch instances on Amazon EC2.
Additionally, students solve problems using AWS resources within a specific price limit. The goal is to teach them the pros and cons of running parallel programs on large datasets using sequential versus AWS EMR.
Project 2 – Cloud Elasticity and Its Aspects
This project enables candidates to gain a deep understanding of cloud elasticity. Their task is to design elastic services using AWS APIs for a dynamically changing load scenario.
Hereafter, they learn to reduce the impact of varying loads on the server using AWS solutions like Auto Scaling Services and Elastic Load Balancing. Furthermore, candidates get to construct their own load balancers and test various catching mechanisms.
As a result, students get to explore various critical cloud computing concepts like on-demand scalability, tolerance, fault detection, and the methods to maximize profit via cost-benefit analysis.
Project 3 – Understanding Cloud Storage
In this project, students delve into the capabilities and limitations of cloud storage technologies. First, they evaluate the drawbacks of traditional file systems and draw a comparison with NoSQL databases (like HBase) and relational databases (like MySQL).
Hereafter, candidates learn data sharding and replication of a simple key-value store and how to deal with consistency problems in geo-replicated key-value stores. They also get to build social network timelines via heterogeneous back-end storage systems. You can go for AWS Cloud Practitioner Certification training and boost your learning experience.
This project also covers numerous storage systems like NoSQL databases, low-latency KV stores, and in-memory databases like Amazon RDS, Apache HBase, DynamoDB, etc. Apart from this, they get to perform Data Warehousing through Online Line Analytics Processing (OLAP) systems like Impala and AWS Redshift.
Project 4 – Using Programming Models
Students learn to develop applications via programming models like Samza, GraphLab, Spark, and MapReduce. Using Apache Hadoop, they can write their own MapReduce code and provision instances on Amazon EC2.
By doing so, they can create their own input text predictor, like Google Instant, from a large text corpus by creating a list of n-grams, generating a statistical language model, and developing a user interface.
Students also gain exposure to iterative programming models by applying the PageRank algorithm on GraphLab and Apache Spark. They shall also learn the methods of dealing with streaming data in order to perform real-time processing across multiple data streams.
Team Project – Building a Web Service for Twitter Analytics
Here, students get to work in teams in order to design and implement a fully functional web service that runs using the REST interface. It must respond to queries by running an analytics job on a large Twitter data set of 1TB, stored in a database like HBASE, MySQL, etc.
Candidates are allowed to use various services and tools to develop the web service. However, it must meet all the requirements. Their work is evaluated via a load generator for a specific period of time by calculating the total cost of AWS services used and the system’s overall performance.
Now, there is an upper threshold for using this budget. Students are disqualified if their systems cross the budget limits. The results are declared depending on how their systems perform in comparison to the baseline.
How to Prepare for Cloud Computing Exam?
Mentioned below are some of the best ways to prepare for a cloud computing exam:
- Have a clear idea of the cloud computing syllabus. This will tend to differ a bit depending upon the certification you choose.
- Take help from digital self-paced study materials. They cover several parts of the cloud computing syllabus like cloud security, networking, machine learning, etc. and are often available for free.
- Set specific study timings. By doing so, you can cover all aspects of the syllabus in a systematic way.
- Take practice certification exams to get an idea of what you may face while appearing for the real one.
- Practice using the platform for in-depth knowledge.
- Connect with an online community. This will help you get study tips, insight into question patterns and even the best ways to answer certain questions.
- Enroll in a cloud computing certification training course. It will provide you with professional guidance, study materials, mock tests, access to the platform and much more, which can help you ace the exam.
Tips to Pass the Cloud Computing Exam
Here are some tips you can follow to ace the cloud computing exam in your first attempt:
- Thoroughly go through the exam guide.
- Familiarize yourself with all aspects of the syllabus.
- Read the certification whitepapers.
- Allocate a fixed time for answering each question.
- In case you are in doubt, flag your answer and review it later.
- If you are a non-native English speaker, you are eligible to get an extra 30 minutes to finish the exam. Do opt for it if you are eligible.
Conclusion
Now that you know the cloud computing syllabus, all that is left for you to do is opt for a certification course. Checking the KnowledgeHut Cloud Computing syllabus will help you master the fundamentals of the Amazon Web Services platform and identify the right services for each problem with ease. Apart from this, we have several other courses that can help you tread on the career path of a cloud professional.
