It is a question that rankles every data science and machine learning enthusiast who wants to upskill and take up MOOC specialisations to land a data science job. Most self-taught machine learning and data science practitioners have to tread the self-learning path with a bunch of online courses, especially through Coursera and Udacity Nanodegree programme. These courses also serve as preparatory material for graduate courses.
While there is no definite consensus on which course is better, it all depends on individual goals and whether students are geared towards a theoretical learning environment or prefer a more job-oriented, hands-on approach. Most of the time, learners fall back on ratings and reviews to gauge the effectiveness of the program and whether it is worth the ROI. Both the platforms are helmed by industry stalwarts – Udacity was founded by Google X founder and ex-Stanford professor Sebastian Thrun, and Coursera is helmed by Andrew Ng.
Job-Oriented Training: Udacity is one of the most preferred platforms for Data Science Nanodegree and for Introduction to Machine Learning. Since the courses are created by big tech firms like Google, Amazon, AT&T, Cloudera and Facebook, Udacity graduates are already working at leading companies like Salesforce, Verizon, Goldman Sachs, Intuit, Accenture among others. In 2016, Sebastian Thrun, co-founder of Udacity pegged the platform as the best path to get a job within six months of graduation. He also announced a 100 percent tuition refund if it didn’t happen.
Hands-On Course: Udacity courses also feature five to six projects which help in giving a hands-on experience. Another key feature of Udacity courses is that they are self-paced and you can finish the course in a short span of time.
Nanodegree Credentials Offer Access To Job Opportunities: The Nanodegree credentials in data science, AI, NLP, computer vision, deep reinforcement learning and data foundations are offered by leading companies like Nvidia, IBM Watson, Amazon, Affectiva, Google, Alteryx, GitHub and AT&T, among others. Besides imparting industry-relevant skills, Udacity’s Nanodegree program also offers exclusive employment opportunities. Their career services team works directly with students to help land jobs at partner companies. (To find out more about the Nanodegree programs, click here.)
Data Analyst Program: The Data Analyst Nanodegree was one of the first online programs to launch which aimed to deliver the right skills needed in the data science career. It also comes with student services and their projects have won rave reviews. According to a post on freecodecamp, the projects are reviewed by paid project reviewers.
Cost Factor: The new Nanodegree Plus program is touted as a definite job guarantee for eligible students in the US and trains them in the most in-demand skills such as Blockchain developer, Android and iOS developers, at a fraction of the cost of a traditional education.
Best Introductory Course For ML: Given that the course has been designed by AI heavyweight and pioneer Andrew Ng, learners who have a background in statistics and programming can understand the concepts very well. However, 40 percent into the course, the learning curve does get steep and that’s where most students get stuck with programming assignments. Even though the course says it doesn’t require prerequisites, a non-math or statistics learner will struggle with the course, unless they brush up on Linear Algebra.
Steep Learning Curve: One of the most common statements ascribed to the Coursera Machine Learning is that it is very theoretical with heavy math and requires a thorough understanding of linear algebra and probability. It also requires basic programming skills, has a steep learning curve, and features rigorous programming assignment and quizzes. In fact, you must commit four to five hours of learning each week if you intend to finish the certification and land a job in the ML field. If you already have a certain level of expertise in the ML field, then Udacity’s AI Nanodegree on AI is highly recommended as a next step to advance skill set.
Data Science Course: Created by Johns Hopkins University, the Data Science Specialisation covers ten modules in the data science right from data collection to data cleaning, exploratory data analysis, R programming. One common refrain about Coursera’s 10-part Data Science module is that they are all R-based and are best suited for beginners who are completely new to data science. However, those who have a programming background and knowledge of R would not find the course very useful.
Job Prospect: Coursera courses too are pegged as a pathway to employment and is the best resource for working professionals to upskill. Since the modules are project-oriented, learners have the flexibility to work on a range of projects that add to the resume. Coursera has definitely increased the career prospects of many students.
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