Naïve Bayes
Ensemble of Learners
Training and Tuning Models
Regression
Decision Trees
Perceptron Algorithms
Support Vector Machines
Evaluation Metrics
One course project-Find Donors for CharityML
Online
3 Months
Quick facts
particular | details | |||
---|---|---|---|---|
Collaborators
Amazon Web Services,
+1 more
|
Medium of instructions
English
|
Mode of learning
Self study, Virtual Classroom
|
Mode of Delivery
Video and Text Based
|
Learning efforts
10 Hours Per Week
|
Course overview
The Intro to Machine Learning with PyTorch certification course is an online self-paced programme designed for candidates who have a keen interest to learn new ideas in the field of technology. The demand for Machine Learning engineers is higher than the supply. Thus, this course has been curated for those who want to strive and stay firm in the competitive market. This is an online self-paced program by Udacity.
Candidates will learn, understand, create and implement the most predictive algorithms in the real-time world. The candidate will deal with both supervised and unsupervised learning. They will have a deep understanding of Neural Networks. The course has a high demand because of its portable and dynamic nature.
Additionally, the 3-course projects engaged in this Intro to Machine Learning with PyTorch training will help the participant to develop a detailed and elaborated knowledge of this subject. It will serve as an opportunity to understand the importance of machine learning with PyTorch in detail.
The highlights
Online self-paced learning
3 months course duration
Projects based
Real-world projects from industry experts
10 hours/week time investment
Certification by Udacity
Program offerings
- Project feedback
- Real-world projects
- Project reviews
- Personal career coaching
Course and certificate fees
The Intro to Machine Learning with PyTorch certification fees can be paid by the user under two different plans - Pay Upfront and Pay as you go.
Intro to Machine Learning with PyTorch Fee Structure
Description | Amount in INR |
Pay Upfront | Rs. 58,257 |
Pay as you go | Rs. 22,849 per month |
certificate availability
certificate providing authority
Eligibility criteria
Work Experience
Candidates willing to apply for the Intro to Machine Learning with the PyTorch programme should have a minimum programming experience of 40 hours.
He/she should have experience with libraries namely Pandas and NumPy.
Education
The candidate needs to have a basic knowledge of statistics and probability. He/She should possess knowledge on how to calculate variance and mean of a probability distribution. The candidate should be familiar with lists and dictionaries
Certification Qualifying Details
The estimated course duration is 3 months. During this duration, the candidate will learn about Machine learning with PyTorch. The syllabus includes three topics which are needed to be covered for the duration of 3 months. Each topic is combined with the one-course project for a better understanding of this subject. The candidate has to devote 10 hours per week in order to complete the program successfully. The Intro to Machine Learning with PyTorch certificate by Udacity will be awarded, thereafter.
What you will learn
After the completion of this Intro to Machine Learning with PyTorch certification syllabus, the candidate will learn the following-
- The core idea of machine learning, and Python
- Comparison between regression and classification
- Understand the concept of decision trees
- Create an image classifier on their own
- Learn to apply Bayes’ rule to predict cases of spam messages
- Build professional presentations
- Implement image classification application using deep neural network
- Learn to use PyTorch
- Understand the Gaussian mixture models and its use
- Learn to manage the access using the different tools
- Master the best practices for a real-time world
- Understand the basics of clustering
Who it is for
This course can be ideal for all those candidates who want themselves to be on their pathway to becoming ML Engineers or Python Programmers.
Admission details
Intro to Machine Learning with PyTorch admission requires the candidate to undergo the following steps-
Step 1- Visit the official website of the programme https://www.udacity.com/course/intro-to-machine-learning-nanodegree--nd229
Step 2- Click on Enroll Now button on the top of the page.
Step 3- You will be directed to a page wherein both payment options namely, Pay Upfront and Pay as you go is given.
Step 4: Choose the desired plan. Regular users will have ‘Regular Student’ button on their page while new users will have ‘Quick Checkout’ as option.
Step 5: Select Quick Checkout and then sign up with your Google or Facebook ID.
Step 6: Then a page will come wherein all the details of fee payment will be given. If you have coupon code then apply it and click on checkout or else directly click on continue with checkout.
Step 7: The payment will be made by the user with debit card, credit card, net banking and others.
Step 8: After doing the payment, a transaction slip will be shared. Then you will be able to check the course and access it.
The syllabus
Supervised Learning
Neural Networks
Introduction to Neural networks
Deep Learning with PyTorch
Training Neural Networks
Implementing Gradient Descent
One course project- Build an Image Classifier
Unsupervised Learning
Dimensionality Reduction
Hierarchical and Density Based Clustering
Clustering
Gaussian Mixture Models
Scholarship Details
Participants applying for Intro to Machine Learning with PyTorch classes can do so by visiting the link https://udacity.zendesk.com/hc/en-us/categories/360002443511-Scholarship-Programs. The candidate needs to then see whether he/she is eligible for scholarship. Hence, it is essential to sign up and submit the information after clicking ‘Notify Me’. Post this, the candidates will be regularly sent notifications for the scholarships posted on the website.
How it helps
The demand for machine learning engineers is far more than the supply. Health care sectors, finance to market predictions, and many other industries are changed by machine learning. A candidate with appropriate knowledge of the same will have great career advancements.
This Intro to Machine Learning with PyTorch certification benefits by helping the learner to know about the foundational machine learning skills which can be applied in the real world. The machine learning techniques taught in the course can be applied to various tasks such as image classification and customer segmentation. Several learning algorithms applications learnt in the duration of the course will enable the learner to demonstrate skills in a better manner. It will help enhance the practical skills needed to start.
Instructors
Ms Cezanne Camacho
Instructor
Freelancer
M.S, Other Masters
Mr Mat Leonard
Instructor
Freelancer
Ph.D
Mr Luis Serrano
Instructor
Freelancer
Ph.D
Ms Jennie Kim Eldon
Product Lead
Udacity
Mr Andrew Paster
Instructor
Udacity
Mr Dan Romuald Mbanga
Instructor
Amazon.com Inc.
Mr Sean Carrell
Instructor
Freelancer
Ph.D
Mr Josh Bernhard
Data Scientist
Freelancer
Mr Jay Alammar
Instructor
Freelancer
Other Bachelors
Ms Jennifer Staab
Professor
Freelancer
Other Masters, Ph.D
FAQs
A tablet is not recommended as they have less computing power. However, OS X, Linux laptops or desktops and modern Windows will work well. The necessary instructions will be provided to install the required software packages in the same.
The applications and programming languages that will be used for this nanodegree program include Scikit-learn, NumPy, PyTorch, Python, Anacondas, Panda and Jupyter Notebook.
A computer with a 64-bit operating system with 8GB of RAM will serve the purpose the best. It will also have an administrator account permission which should be enough to install programs including Anaconda with Python 3.x.
Basic knowledge of statistics and probability along with Intermediate Python programming knowledge is recommended before enrolling in this course. In case someone does not fulfill the requirements, a few other courses like Intro to Data Science will help one prepare for this program.
A seven-day free trial session has been planned. The candidate may scroll down the page to reach the fee details information. Start free trial option will be available. Click on it and proceed to enjoy your free trial sessions.