Learn to build Machine Learning Algorithms In this Udacity Machine Learning review, I will talk about how Udacity will help land a job as a Machine Learning Engineer ★ ★ ★ ★ ★ 40% Off on all Nanodegrees GET THE DEAL

Hi there, today I am going to take you through the entire Udacity machine learning nanodegree review right from the course syllabus to the reviews of earlier machine learning nanodegree graduates.

So keep reading.

This course is intended for students with knowledge of Python and ML algorithms, hence, if you are new to this, I suggest to look for the intro courses.

For this article, I have to spend a dozen hours to identify whether the course is truly recommendable to you or not.

1.How many have benefited from this course?

2.How many have landed a successful job after completing this course?

Hence I decided to write this complete analysis of Udacity Machine learning Nanodegree.

My end goal was to identify whether the Udacity machine learning nanodegree was worth it.

Like several machine learning courses, this one also requires some prerequisites like python and basic machine learning.

We will discuss all the prerequisites of this course later section.

Out of all the reviews that I read over social media, one thing all the nanodegree graduates praised was Udacity’s project review system and career support for this course.

One of the earlier machine learning nanodegree graduate Balaji M.J. who has taken both Udacity machine learning nanodegree and Coursera’s machine learning specialization writes about Udacity on Quora.

Here’s the screenshot of it

Many people ask me this question, how is Udacity machine learning nanodegree compared to that of Coursera’s machine learning specialization?

According to Logan Spears who is a graduate from both , says that it’s good to take both courses, starting with Coursera to build a strong conceptual foundation and further refine skills by doing practical projects at Udacity.

In case you have limited time and money he suggests to go with Udacity.

Here are his both certificates

Udacity Machine Learning Engineer Nanodegree

Coursera Machine Learning Specialization

Let’s dig deep into Udacity machine learning nanodegree review

Udacity’s Machine Learning Engineer Nanodegree program is a reliable alternative to the one from Coursera.

The course will teach a plethora of ML techniques that might help you to complete real-world projects as a machine learning engineer.

Many graduates are satisfied with the quality of projects in the program that they even forked their repos on Github and left solutions up as portfolio items.

The last step in completing this program is to do the capstone project. You are supposed to choose this capstone project on your own.

We shall discuss the entire syllabus in the coming section.

According to some, the greatest motivator is the desire to complete the nanodegree such that you might end up putting lot of efforts than normal.

An ex-ML nanodegree graduate says,

“I ended up creating something of which I am truly proud. Udacity’s program doesn’t so much teach as it does provide a framework and motivation for you to teach yourself.”

Now we shall have a detailed talk on the Programming Environment.

Udacity teaches you ML in modern Python environ with frameworks like Sklearn, Tensorflow, and Keras.

Also, you are taught to use AWS in deploying machine learning software to the cloud.

This is not the case with Coursera’s specialization. ML on Coursera is taught in the “OG” 3D math language and Matlab.

As Matlab is a costly affair, machine learning is mostly done on Python today.

Because of this reason many prefer Udacity as it provides industry best practices for students to get a job-ready profile.

Now the next section covers pricing and duration of the nanodegree

I hope you are enjoying this Udacity Machine Learning Nanodegree Review.

Udacity Machine Learning Nanodegree Price

With the given amount of offerings from Udacity in terms of content and dedicated support, the Machine Learning Engineer Nanodegree comes with a flat fee of $399.

You are required to complete this in a period of 3 months expecting that you will learn at least 10 hours per week.

Cost: $399

Duration: 3 months

You can also pay monthly at a cost of $199/month.

According to me, given the quality of instructor feedback, such a high price also seems reasonable as there are highly educated mentors who meticulously review your projects.

In case you have made up your mind to enroll, you can sign up here

Who are the instructors?

Udacity has the finest knowledgeable instructors that can guide you through all the complex concepts of machine learning.

Here’s the list of them,

1.Cezanne Camacho-Master’s in Electrical Engineer at Stanford

2. Mat Leonard– Physicist, neuroscientist and data scientist from the University of Berkeley

3.Luis Serrano– Machine Learning Engineer at Google

4. Dan Romuald Mbanga-Lead at Amazon’s AI business development

5.Jennifer Staab-Statistician and computer scientist with RTI

6.Sean Carrell-University of Waterloo, Canada

7.Josh Bernhard- Data Scientist at Nerd Wallet

8.Jay Alammar-Investment Principle at STV

9.Andrew Paster– Engineer from Yale

Getting taught by such experienced instructors is exciting.

Isn’t it?

Now lets shade some light on the pre-requisites of the course.

Prerequisites of the Machine Learning Nanodegree Program

In order to squeeze more out of this program, you should have the knowledge of the following topics

One should be an intermediate python programmer who has at least 40 hours of programming experience in Python. If you are new to python, I recommend you to take a free python course on Udacity here.

Along with Python programming, you should be familiar with data structures like dictionaries and lists which are integral parts of Python itself and should have hands-on experience with libraries like NumPy and pandas

Apart from Python, you are required to have an intermediate understanding of machine learning algorithms which includes Supervised learning models, Unsupervised models, and Deep learning models

In short, this program is intended for students who already familiar with machine learning algorithms.

The best part about the program I found is that while going through the program if you have questions about anything, you can directly reach the support team at machine-support@udacity.com.

That’s all about the pre-requisites, let’s have a look at the course syllabus

Syllabus of Machine Learning Engineer Nanodegree Program

The entire nanodegree program is divided into 4 courses followed each followed by respective projects.

All the projects are meticulously crafted to showcase your skills and build a career portfolio that defines your ability to write complex machine learning algorithms and model deployment.

Let’s have a closer look at each course.

The first course is Software Engineering Fundamentals

In this program, you have to understand how to build ML algorithms and use them for scalable, production systems. To begin with, you need to understand how to write a production-level code. Writing your own python package will train you for this.

Project1:Build a Python Package

Here you will have to write production-level code and practice object-oriented programming that can help you to build machine learning projects.

This project will demonstrate your skills in Object-oriented programming, Clean and modular code and Code documentation

The second lesson is about Machine learning in production.

In this lesson, you will use Amazon SageMaker to deploy machine learning models to a production environment

The purpose of this lesson is to teach you how to predict the sentiment of a user using Amazon SageMaker(User who provides a movie review.You need to predict whether the movie review is good or bad).

Also, you will be allowed to create a simple web app that will use your deep learning model and can accept input from a user.

Project 2:

Using recurrent neural network you have to predict the sentiment of a movie review with the help of a dataset of text from IMdB.

This model will be deployed using Amazon SageMaker.

As discussed above, you need to create a web app that will take user input.

The next is a Machine Learning case study

This lesson is dedicated to helping you learn ML techniques on real-world examples.

Project 3 : Plagiarism Detector

In this project you have to use your machine learning skills to check whether the two text sources are similar, in short, you need to identify any cases plagiarism.

With the help of Amazon SageMaker, you need to deploy a plagiarism-classification model

You have to extract certain features from a text and develop a model for plagiarism detection.

Capstone Project

In this capstone lesson, you’ll choose a machine learning challenge and apply a proper solution.

Here you will use your entire knowledge of the program to build a machine learning project of your choice.

Define the problem, investigate, identify and explore the data, then perform your analysis and come to a conclusion. Post this conclusion at your GitHub repository.

This project is of paramount importance in building your portfolio as a machine learning engineer.

Udacity Machine Learning Nanodegree Reviews

Great Learnings

★ ★ ★ ★ ★

“Challenging but very interesting experience going from Stage 0 to work with the data, understand models along with writing the code

– Rajesh Chaurasia





Practical approach

★ ★ ★ ★ ★

I completed the Machine Learning Engineer Nanodegree course at Udacity. I learned advanced machine learning techniques and algorithms and how to package and deploy my models in a production environment. I had hands-on experience using Amazon SageMaker to deploy trained models to a web application and evaluate model performance

– Murilo V





Awesome projects

★ ★ ★ ★ ★

Ending the month of February with another completed course! Nanodegree from Machine Learning Engineer. I learned how to develop and deploy machine learning and deep learning models in the AWS environment, develop feelings analysis models and plagiarism detection, deliver packages in PyPi, and improve skills already developed.

–Matheus Sena Vasconcelos

You can find his capstone project here

One of the most interesting Capstone project I found was the Dog Breed Classification by Rahul

You can find his complete project on Github here

Machine Learning Dog Breed Classification Capstone Project

Here’s one more from Praveen Bandaru

Analysis of Machine Learning Nanodegree

So in a nutshell, I would say the course gives a better hands on experience on machine learning projects.

If you have some knowledge about machine learning, this course is a good source to practice your machine learning concepts.

As ML is an ever-growing field, it is one of the hottest jobs of the 21st century and this is the right time to make a decision.

At the end I would say ‘Yes’ to this nanodegree.

I hope I have convinced you a bit. I did my job, it’s time for you to take the action.

If you are planning to enroll later,I request you to comeback and buy the course through the links here. This will help me keep the blog running and write more articles to help learners like you.

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Akshay Vikhe I am a aspiring data scientist with huge interest in technology. I like to review courses which are genuine and add real value to students career

Summary Author Rating Aggregate Rating 5 based on 4 votes Brand Name Udacity Product Name Machine Learning Engineer Nanodegree Price $ 399 Product Availability Available in Stock