Machine learning is taking over the world - it is benefiting companies across industries. It is helping organisations create systems that can understand, learn, predict, adapt, and operate on their own. Thus, understanding how machine learning works is one of the most valuable and useful things you can do.
Whether you’re launching a career, advancing a career, or just excited to learn a new skill, there is no time like the present to get started on a Machine Learning path. This Foundation Nanodegree program offers everything you need to kickstart your Machine learning journey—with no prior programming skills required.
Get started with this Foundation Nanodegree Program to prepare for a career-ready Nanodegree Program
Get started with programming through interactive content like quizzes, videos, and hands-on projects. Our learn-by-doing approach is the most effective way to learn to code.
Advance quickly and successfully through the curriculum with the support of expert reviewers whose detailed feedback will ensure you master all the right skills.
Draw inspiration and knowledge from dedicated slack forums. Stay on track with mentors who will help in case of any doubts or when you are stuck with projects.
Learn the skills needed to enroll in to a job-ready Nanodegree program and launch your career into this field. Also, get cashback which you can use for enrolling into the next Nanodegree.
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In order to succeed, we recommend having experience using the web, being able to perform a search on Google, and (most importantly) the determination to keep pushing forward!See detailed requirements.
Concepts of Python programming. Configuration of development environment. Standard library functions. Variables and strings. Functions, control flows and loops. Structured data: list and for loops; how to fix the problemExplore Bikeshare Data
Research methods and visualization of data. Concentration trends. Variability and standardization. Normal distribution and sampling distribution. Statistical tests: hypothesis test, T test, ANOVA, chi-square test. Regression and correlationAnalyze a Perceptual Phenomenon
Data analysis process: Learn how to use data to answer questions. NumPy and Pandas operations for one-dimensional data. NumPy and Pandas operations for two-dimensional data. Data modelling: Understand the basic types of data and learn how to handle data setsExplore the dataset
Learn how to use the accuracy rate or recall rate and other indicators to test and measure to improve performance.Forecast Prices
Arpan likes to find computing solutions to everyday problems. He is interested in human-computer interaction, robotics and cognitive science. He obtained his PhD from North Carolina State University, focusing on biologically-inspired computer vision. At Udacity, he spends a good chunk of time designing interactive exercises for his courses, besides working on pet projects to improve or automate workflow.
David Joyner completed his Ph.D. in Human-Centered Computing at Georgia Tech specializing in delivering automated feedback and assessment to students in exploratory learning environments. He joined Udacity to develop exercises, projects, and (one day!) entire courses that adapt to the learner's ability and progress.
With a PhD in Mathematics from the University of Michigan, Luis has worked as a mathematical researcher and university professor and as a Machine Learning engineer at Google, where he applied predictive algorithms to generate recommendations for YouTube
Scientist, educator, inventor, and entrepreneur, Sebastian led the self driving car project @ Google X and founded Udacity, whose mission is to democratize education by providing lifelong, on-demand learning to millions of students around the world.
Vincent Vanhoucke is a Principal Research Scientist at Google, working with the Google Brain team on deep learning research and infrastructure. He completed his Ph.D. at Stanford University on speech recognition, and now focusses his research on image and video understanding as well as mobile and robotic perception.
An experimental physicist by training, Katie first got interested in machine learning by using it to search for new particles like the Higgs boson. Since nobody should need a PhD in physics to play around with machine learning, though, she leapt at the chance to teach others about using data analysis to solve interesting problems. When not discovering new particles or teaching, she’s usually trail running or bribing her deskmate’s dog with treats.
Truly world class and real-world projects yet covers all the essential basic constituents from a academic perspective.
Wonderful. Covered most of the topic.
Superb primer for newbies
It has been a great experience of gaining knowledge.You get to learn more things while you complete your project.The lessons are awesome and well-explained.
To make it even easier to learn, you can finance your Nanodegree through Affirm.
As low as US$ 0 per month at 0% APR.
Pay your monthly bill using a bank transfer, check, or debit card.
7 days refund; no questions asked
Time to Complete: 5 months
Prerequisite: Prior programming experience is not required.
Offer: Get ₹4000 credit on completion of the Machine Learning Foundation Nanodegree. Use the credit for a new enrollment in any other Nanodegree
Admissions Closes: 21 October, 2018
* Price exclusive of taxes. GST of 18% gets applied on checkout. Option to convert your payment into EMI available on checkout page.
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