- Tensors 1D
- Two-Dimensional Tensors
- Derivatives In PyTorch
- Dataset
Beginner
Online
5 Weeks
Free
Quick facts
particular | details | ||
---|---|---|---|
Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
|
Learning efforts
4-5 Hours Per Week
|
Course overview
The PyTorch Basics for Machine Learning certification programme is offered by IBM to arm you with the skills for implementing classic machine learning algorithms. You will get to know how PyTorch is used to optimise and create deep learning models.
During the PyTorch Basics for Machine Learning training, you will learn important models such as linear and logistic regression models. This introductory-level programme will teach you how to train your models and their related concepts like gradient descent, cost and loss.
With the learnings of edX’s PyTorch Basics for Machine Learning course, you will learn to save your training and model in apps like checkpoints, early stopping and cross-validation for hyperparameter selection. Also, basics around the linear object, like their interaction with data with a distinctive number of samples and different dimensions, will be cleared.
The PyTorch Basics for Machine Learning course also includes a final project in the end to assess your skills and performance. You can even get a paid instructor-signed certification after completing the course. The learners also can audit the self-paced programme without paying the fee for a limited duration.
The highlights
- Free access
- Five-weeks course
- An offering of IBM
- Introductory-level programme
- Self-paced learning
- Requires four to five hours of the weekly study
- Data Analysis and Statistics course
- Video lectures in English
- Optional certificate
Program offerings
- Up-to-date curriculum
- Five weeks training
- Offered by ibm
- Online learning
- Free programme access
- Video lectures
- Self-directed learning
- Subtitles in english
- Paid certification
- Final project
- Expert instructor
Course and certificate fees
Type of course
- You can join edX’s PyTorch Basics for Machine Learning course for free.
- If you want a verified certificate, you must pay an amount of Rs. 3,238.
PyTorch Basics for Machine Learning fee structure
Course option | Fees in INR |
PyTorch Basics for Machine Learning (course content audit) | Free |
PyTorch Basics for Machine Learning (content + certification) | Rs. 3,238/- |
certificate availability
certificate providing authority
certificate fees
What you will learn
By the end of the PyTorch Basics for Machine Learning course, you will gain an in-depth understanding of the following:
- Training models in PyTorch
- Training Machine Learning (ML) applications with PyTorch
- Incorporating Python libraries like Pandas and Numpy with PyTorch
- Creating an ML pipeline in PyTorch
- Loading large datasets
- Gain practical knowledge of deep learning
Admission details
Step 1 – Use this https://www.edx.org/course/pytorch-basics-for-machine-learning to open the PyTorch Basics for Machine Learning course page.
Step 2 –Click on the ‘Enroll now’ button and begin the registration process.
Step 3 – You can directly sign in by signing in with your Apple, Facebook, Google or Microsoft account. Alternatively, you can create a new edX account.
Step 4 – After registering, you will now be successfully enrolled in the PyTorch Basics for Machine Learning programme by edX. Now, choose whether you want to audit the course for free or select the paid option.
Filling the form
You need not fill any application form to join the PyTorch Basics for Machine Learning online course. Log on to the edX website, reach the course page and register for an account. You can do this by entering your full name, email ID, public username, country and generating a new password.
Also, you can link an existing account such as Microsoft, Google, Apple or Facebook to register. You will be directly enrolled in the PyTorch Basics for Machine Learning programme by creating an edX account.
The syllabus
Module 1
Module 2
- Prediction Linear Regression
- Training Linear Regression
- Loss
- Gradient Descent
- Cost
- Training PyTorch
Module 3
- Gradient Descent
- Mini-Batch Gradient Descent
- Optimization in PyTorch
- Training and Validation
- Early stopping
Module 4
- Multiple Linear Regression Prediction
- Multiple Linear Regression Training
- Linear regression multiple outputs
- Multiple Output Linear Regression Training
Module 5
- Linear Classifier and Logistic Regression
- Logistic Regression Prediction
- Bernoulli Distribution Maximum Likelihood Estimation
- Logistic Regression Cross Entropy
How it helps
The PyTorch Basics for Machine Learning programme by edX is an introductory-level course, which means you can easily comprehend the Machine Learning concepts along with PyTorch’s know-how. IBM’s top Data Scientist, Joseph Santarcangelo, will be your instructor for the training.
Moreover, you have the option to get the PyTorch Basics for Machine Learning certification by paying a certain fee. This shareable certificate will be signed by the instructor with IBM’s logo to highlight your skills and knowledge, improving your employability.
Instructors
Mr Joseph Santarcangelo
Data Scientist
IBM
Ph.D
FAQs
This course is curated by IBM.
Joseph Santarcangelo, PhD and a Data Scientist at IBM, will be your instructor for the PyTorch Basics for Machine Learning training.
Yes, you can enrol in the course without paying any charges.
The e-certificate will have IBM’s logo along with your instructor’s signature to acknowledge your accomplishment. By sharing it on LinkedIn or adding it to your CV, you can enhance your job prospects. Also, it supports edX as a non-profit organisation to bring such courses online for free.
Articles
Popular Articles
Latest Articles
Similar Courses
Machine Learning Algorithms
Great Learning
Python for Machine Learning
Great Learning
Machine Learning Fundamentals in Depth
Skill Lync
Data Engineering and Machine Learning using Spark
IBM via Coursera
How Google does Machine Learning
Google via Coursera
Machine Learning Introduction for Everyone
IBM via Coursera
Machine Learning for All
University of London, London via Coursera
Fundamentals of Machine Learning
Board Infinity
Managing Machine Learning Projects
Duke University, Durham via Coursera
Fundamentals of Machine Learning for Healthcare
Stanford via Coursera
Courses of your interest
An Introduction To Coding Theory
IIT Kanpur via Swayam
C++ Foundation
PW Skills
Data Science Foundations to Core Bootcamp
Springboard
User Experience Design And Research
UM–Ann Arbor via Futurelearn
Data Analysis with Excel for Complete Beginners
CloudSwyft Global Systems, Inc via Futurelearn
Artificial intelligence Design and Engineering wit...
CloudSwyft Global Systems, Inc via Futurelearn
Data Science Fundamentals on Microsoft Azure
CloudSwyft Global Systems, Inc via Futurelearn
Artificial Intelligence Projects
Great Learning
More Courses by IBM
R Programming Basics for Data Science
IBM via Edx
Threat Intelligence Lifecycle Fundamentals
IBM via Edx
Introduction to Data Engineering
IBM via Coursera
Relational Database Administration
IBM via Coursera
Introduction to the Threat Intelligence Lifecycle
IBM via Coursera
Introduction to Web Development with HTML CSS Java...
IBM via Coursera
Introduction to Devops
IBM via Coursera
Data Scientist Career Guide and Interview Preparat...
IBM via Coursera
Data Analyst Career Guide and Interview Preparatio...
IBM via Coursera
Trending Courses
Popular Courses
Popular Platforms
Learn more about the Courses
The Brochure has been downloaded and sent to your registered email ID successfully.
Thank You!
Brochure has been downloaded.
Sign In/Sign Up
We endeavor to keep you informed and help you choose the right Career path. Sign in and access our resources on Exams, Study Material, Counseling, Colleges etc.