A machine learning engineer is a computer scientist who specializes in developing algorithms and models that allow computers to learn from data. Machine learning is a key technology behind many of the artificial intelligence applications that are transforming our worlds, such as self-driving cars, facial recognition, and fraud detection.
Microsoft Azure is a cloud computing platform that offers a wide variety of services for businesses, including machine learning. As a machine learning engineer for Microsoft Azure, you will be responsible for developing and deploying machine learning models on the Azure platform.
You will work closely with customers to understand the problem they want to solve, and then develop a solution that meets their needs. You will also be responsible for developing internal tools and features to help customers easily create and deploy their own machine learning solutions.
In this Nanodegree program, Students will improve their experience by building and deploying sophisticated machine learning solutions using open source tools and frameworks, and gain experience running complex machine learning tasks using the Azure labs accessible within the Udacity classroom.
Udacity is an online company that provides a variety of online courses that cover various educational topics. It was founded by Sebastian Thrun, David Stavens, and Mike Sokolsky. Udacity was started in 2011 with free computer science classes by Stanford University. Udacity offers a range of courses, such as free and paid courses that require online certification, such as Nanodegree programs.
Some of the unique features you will find at Udacity cannot be found anywhere else. These unique features are what actually make Udacity one of the very best platforms by which you can enroll in an online course.
- Real-world projects from top industry experts
With real-world projects and engaging content created in collaboration with top-tier firms, you’ll master the IT skills that employers demand.
- Technical Support by mentors at Udacity
The Smart and knowledgeable mentors at Udacity will guide your learning and are always available to answer your questions, help you and keep you on track
- Career services
You’ll have access to GitHub portfolio reviews and LinkedIn profile optimization to help you develop your career and obtain a high-paying position.
- Learn with your own freedom
Create a learning plan that matches your busy schedule. Learn at your own speed and on your own timetable to achieve your specific goals.
Class content – Real-world projects, Project reviews, and Project feedback from experienced reviewers
Student services – Technical mentor support, Student Community
Career services – Github review, Linkedin profile optimization
Meet Your Instructors
- Noah Gift – Founder of Pragmatic AI Labs
- Alfredo Deza – Instructor
- Erick Galinkin – Principal AI Researcher | Rapid7
- Soham Chatterjee – Graduate Student at the Nanyang Technological University
To reach success in this program, you ought to be intermediate in completing Python programs and SQL queries. Intermediate Python programming knowledge, of the sort gained through the Programming for Data Science Nanodegree program, programs, or another introductory programming course, can be confirmed through additional real-world software development experience.
Now let’s come to the most important part of the course which is the course itself and what you get in it when you enroll in this course. This Course has a total of three sections each explaining some important topics related to the course and providing with you learning points and real-world projects at the end. Let’s take a deep dive into the sections -:
Working with Azure Machine Learning
Machine learning is a critical business function for many corporations. Find out more about the use of Azure Machine Learning and how to build a machine learning pipeline in it.
In this project, we cover many different ways to work with data and machine learning. It can be tough to determine which approach to take — building a personalized machine learning pipeline, employing AutoML, hyperparameter tuning, and so on. During this project, students work with scikit-learn, Hyperdrive, and AutoML to discover the advantages and disadvantages connected to each technique.
Students will then use the same dataset for an ML Auto-TUNE run to find an optimal model and set of hyperparameters. Finally, students write a README outlining their findings and comparing the differences between, the costs, and benefits of the different algorithms they employed.
Machine Learning Operations
This course covers the key concepts of operationalizing machine learning, including selecting the appropriate targets for deploying a model, using Application Insights, diagnosing errors in log data, and harnessing the power of Azure’s network pipelines.
MLOps and its core features have been discussed in this course in detail. This project will use all the knowledge acquired in the lessons to build a model to be trained with AutoML and deployed in a production environment. You will use Azure to configure a cloud-based machine learning production model, deploy it, and use it. You will produce, publish, and consume the pipeline. In the end, you show all your work using readme file and screencast videos.
The capstone project gives you the opportunity to utilize the knowledge you have acquired from this program to address a captivating dilemma. You will have to utilize Azure s Automated Machine Learning and HyperDrive to tackle a challenge. Finally, you will have to deploy the model as a service and test the model URL.
According to the Program, the course is expected to be completed within approximately 3 months if you devote a minimum of 5-10 hours per week to the course. As we mentioned above, they have a self-paced learning environment, so you can attend at your discretion and at your pace.
If you take more than 3 months to finish the course, you have to take the monthly pay-as-you-go plan and pay extra which will increase your overall cost of the course.
Now let’s talk about the cost of the course which is an important part of whether you will buy or not buy the course. In this course, Either you will pay for monthly access or you can also choose a 3-Months access plan.
If you choose the monthly pay-as-you-go option you will pay $399 per month and there is another option that you can choose which comes with exclusive discounts which is a 3 months plan that you need to pay upfront and costs you around $1017 which comes with exclusive discounts making it cheaper than the monthly plan and also recommended by Udacity.
If you pay upfront for the 3 months’ access you can save up to 15% + 70% exclusive discounts which you cannot if you take the monthly plan. If you need more time after 3 months, you can switch to a monthly access plan but it will increase the overall cost of the course.
Udacity will give you personalized Discounts if you answer 2 questions and pay upfront rather than a pay-as-you-go plan. You will get a promo code with an exclusive 70% Discount just for you on your course by just answering 2 simple questions.
The course does not have many ratings and reviews as it is a new Course But students have a lot to say about Udacity and its courses. Some of the Udacity-related reviews are -:
“Good Content and Great learning experience. The projects were really practical and best to do hands on, The overall partnership with udacity and nutanix was great, The instructors were very well versed with the topics.”-Yatharth S.
“I do like their marketing course as they have provided exercises for students to practice on. Unlike any other course, which only teach about theory and key points, Udacity ensures student can apply the new knowledge in the workplace..”– Luka S.
“The projects. They are challenging, and when completed result in a great sense of accomplishment. The quality of the lessons are also great. It’s great that the sequence of projects allow one to vreate a portfolio that could be used for interviews”– Albert J.
“udacity is a fortress of knowledge, trial and error, revision, and real projects similar to professional work in companies and organizations when hiring with the provision of the latest information about the field from experts and deep details.”– Ahmad J.
Machine learning is one of the most in-demand skills in the tech industry. A machine learning engineer is a professional who specializes in developing and deploying machine learning models. Machine learning engineers are in high demand due to the increasing popularity of machine learning. The average salary for a machine learning engineer is $146,000.
This is overall a good course created by experts at Udacity and also the features and offers provided by Udacity make this course a very good Nanodegree program. Also, You should also check other courses which you can take right after this course as those courses are made with help of top tech companies, they are of high quality and make you more knowledgeable about your field. If you are interested in other Udacity courses, please check out all courses on our website.
The course also has easy to follow a curriculum that includes everything to build your foundation. And also every section at the end includes a real-world project that will give you practical experience and make you job-ready.
One thing you should keep an eye on is your timing, try to complete your course in the estimated time provided by the course, or else you have to pay more for extra months which will increase your overall cost of the course.
If you think that the Udacity Machine Learning Engineer for Microsoft Azure Nanodegree Course is right for you, Udacity is the perfect place for you to take the course and land your dream job.