Deep Learning: Mastering Neural Networks
Course Overview
Deep learning has transformed how organizations analyze data and make data-driven decisions, making it crucial for professionals to gain AI-related skills to stay competitive. This 8-week course from MIT xPRO offers you a comprehensive introduction to this field, combining theory and hands-on practice. You will gain skills and tools like Python to design and optimize neural networks for classification, regression, and sequential data processing. Also, master techniques like transfer learning, convolutional (CNN) and recurrent neural networks (RNN).
Program Highlights
Python tools and libraries to build training neural networks
Deep Neural Networks: GANs and Transformers
Guided cases studies about Deep Neural Networks
Learning methodology that allows participants to practice their newly acquired skills, with one live session every two weeks for guidance and Q&A
Networking with fellow participants to share experiences and build collaborative relations
Certificate in Deep Learning in addition to 4.8 Continuing Education Unit (MIT CEUs)
Who is this virtual course for?
The course is designed for experienced professionals looking for a deeper understanding of neural networks and their applications. This program is best suited for:
Software engineers and developers aiming to build and optimize AI-driven applications.
Data scientists and analysts looking to deepen their expertise in AI and machine learning.
AI & ML professionals seeking to leverage neural network techniques to solve complex problems with innovative solutions.
Technology professionals eager to explore cutting-edge advancements in AI and deep learning.
Past Participant Profiles
Past learners engaged in this deep learning course have come from diverse industries, roles, cultures, and professional experiences, enriching the program with fresh perspectives. This diversity creates discussions that offer valuable insights and innovative solutions to organizational challenges.
Diverse Functional Responsibilities
A Wide Range of Work Experience
Learning Objectives
Explore the core mathematical and conceptual ideas underlying deep neural networks.
Experiment with deep learning models and algorithms using available machine learning toolkits.
Examine application approaches and case studies where deep learning is being used throughout a variety of industries.
Understand advanced neural network architectures for application in software products.
Gain strategic insights into AI and its potential impact on business models.
Course Outline
History of Machine Learning
Overview of Key Machine Learning Concepts
Linear and Logistic Regression Algorithms
Perceptrons and Neural Networks
Gradient Descent-Based Learning
Introduction to Coding Tools
Basics of Python
Overview of Data Science-Related Python Libraries
Introduction to Machine Learning using Python
Python Classes
Overfitting vs Generalization
Training Curves
Train/Validate/Split
Dropout
Data Encoding
Neural Networks: Multilayer Perceptrons (MLPs)
Autoencoders
Convolutional Neural Networks (CNNs)
Deep Neural Networks
Transfer Learning
Sequence-to-Sequence Mapping
Recurrent Neural Networks
Generative Adversarial Networks (GANs)
Transformers
Large foundation models: GPT-3
Case Study: CNNs and Tire Defects
Case Study: Natural Language Processing and BERT
Case Study: GPT-3
Case Study: Emergence
Case Study: Ethics
Capstone Project and Culmination of the Course
Identify a potential business problem or challenge that could be solved or improved through deep learning
Apply the knowledge gained throughout the course by creating a deep learning model
A basic knowledge of programming languages is a prerequisite for this program. The course will, however, explain the necessary foundational concepts of machine learning and programming, allowing those without previous experience to participate fully.
Key Takeaways
Learn the essentials of building neural networks.
Develop an understanding of how Python works with machine learning models.
Define and train neural networks and metrics.
Use autoencoding to customize neural networks.
Apply transfer learning for advanced applications.
Train deep learning GANs and Transformers.
Learn through case studies how to apply deep learning models to solve organizational challenges.
Certificate of Completion
All participants who successfully complete the Deep Learning: Mastering Neural Networks course will receive an MIT xPRO Certificate of Completion. In addition, they will earn 4.8 Continuing Education Units (MIT CEUs).
Participants are required to complete a CEU confirmation form based on the number of learning hours in each course to obtain CEUs
Meet your instructor
Clarence J. LeBel Professor in Electrical Engineering, and Professor of Electrical Engineering and Computer Science in the EECS Department at MIT
What Past Learners are Saying
FAQs
How do I know if this program is right for me?
Once you've reviewed the general program information, complete the form above to access the full course brochure with more comprehensive details about the content, the methodology, and the skills you will gain through your learning experience. If you have any further questions, email us at globalalumni@xpro.mit.edu, and a dedicated program advisor will reach out to guide you through the process.
Are there any prerequisites for this program?
Some programs have prerequisites, especially those with technical content. You’ll find details on the homepage and in the brochure. If you have any questions, feel free to email us. Please note that all programs are taught in English unless otherwise stated, so proficiency is required.
What other dates will this program be offered in the future?
Check back on this program web page or email us to inquire about future release dates.
How much time is required each week?
Each program includes the estimated weekly learner effort in the Duration section at the top of the webpage. You can also find this information in the program brochure by completing the form above.
How will my time be spent?
The program is designed to help you balance your working and study time. This course includes activities such as:
Recorded video lectures from faculty
Webinars and office hours, as per the specific program schedule
Case studies
Periodic tests and lesson activities
Final project if required
Completing your final project, if required For more information on program activities, please email us.
What are the requirements to earn the certificate?
To earn your certificate, you must complete all activities, tests, and meet the weekly time commitment. Some programs also include a final project or assignments. Check the required time in the Duration section at the top of the program webpage. For more details, fill out the form for the brochure or email us at (Email account).
What type of certificate will I receive?
Upon successful completion of the program, you will receive a digital certificate, which you can share with friends, family, schools, or potential employers. You can also use it on your cover letter or resume and display it on your LinkedIn profile. The digital certificate will be sent approximately two weeks after you finish the program and the grading is complete.
Can I get the hard copy of the certificate?
Note that only verified digital certificates will be issued upon successful completion, which allows you to share your credentials on social platforms such as LinkedIn, Facebook, and Twitter.
How long will I have access to the learning materials?
Participants who have paid for individual courses or multi-course programs will have indefinite access to archived course materials. However, future updates to the course or web environment may limit access to some materials over time. Course assistants, instructors, and live discussion forums may be available for up to 30 days.
What equipment or technical requirements are there for this program?
Participants will need the latest version of their preferred browser to access the learning platform, as they will be required to access documents, spreadsheets, presentations, PDF files, and transcripts.
Do I need to be online to access the program content?
Yes, the learning platform is online, but video content can't be downloaded,. You can still download transcripts, readings, and assignments on any device. Video lectures must be streamed, and live webinars or office hours also require an internet connection. Don’t worry—these sessions are always recorded.
Global Alumni will process payment information, and you will be redirected to a secure website, to complete the payment.
Once payment is completed, you will receive confirmation of your registration within 48 hours. Please, retain this email for possible requests related to this course in the future.
If you are unable to complete the payment, please contact Global Alumni at globalalumni@xpro.mit.edu, and you will be provided with bank account details to complete your payment via transfer.
Requests for cancellation and refunds will be carried out as follows:
a. Participants who wish to unenroll and request a refund may do so within one week (7 days) after the course starts, with $150 administrative fee (except for medical or other justified reasons). The requests made up until the course starts, will not be subject to administrative fees.
b. Communication channel: requests should be made via e-mail at the following address: globalalumni@xpro.mit.edu
For any course purchased as part of a program bundle, learners may only request a refund within one week (7 days) after the start of the first course—regardless of whether that course is sequentially first in the program.
Applicable taxes will be calculated and added at checkout in accordance with country/state regulations.
Didn't find what you were looking for? Schedule a call with one of our Program Advisors or call us at +1 315 501 0457.
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