- A warm welcome from John Cohn, IBM Fellow Watson IoT
- Introduction - Romeo Kienzler
- Introduction - Ilja Rasin
- Introduction - Niketan Pansare
- Course Logistics
- Cloud Architectures for AI and DeepLearning
- Linear algebra
- Deep feedforward neural networks
- Convolutional Neural Networks
- Recurrent neural networks
- LSTMs
- Auto encoders and representation learning
- Methods for neural network training
- Gradient Descent Updater Strategies
- How to choose the correct activation function
- The bias-variance tradeoff in deep learning
Applied AI with Deep Learning
Quick Facts
particular | details | |||
---|---|---|---|---|
Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
|
Course overview
The Applied AI with Deep Learning online course is provided as a part of the IBM advanced data science certification programme for giving much-needed insights into the models of deep learning for students. The Applied AI with Deep Learning certification syllabus will dive into the fundamentals of linear algebra, neural networks, deep learning frameworks and advanced concepts such as time series forecasting, natural language processing and image recognition. The students will be trained at an advanced level of learning and it provides a sharable and verified certificate upon completion. The Applied AI with Deep Learning by Coursera is provided in the English language with subtitles in many languages and the learning can be done easier with flexible deadlines for submission of projects and assignments.
The highlights
- 100% online programme
- Shareable and verified certificate
- Deadlines flexible
- Advanced level course
- Part of Advanced Data Science with IBM specialisation programme.
- The course duration of 25 hours
- Subtitles offered in 10 languages
- The programme provided by Coursera
Program offerings
- Assessments
- Online course
- Readings
- Quizzes
- Video lectures
- Practice exercise
Course and certificate fees
Applied AI with Deep Learning
Particulars | Fee Amount in INR |
Introduction to Git and GitHub (audit only) | Free |
Introduction to Git and GitHub - 1 month | Rs. 4,074/- |
Introduction to Git and GitHub - 3 months | Rs. 8,149/- |
Introduction to Git and GitHub - 6 months | Rs. 12,224/- |
certificate availability
Yes
certificate providing authority
Coursera
Eligibility criteria
Education
Candidates must have coding skills in Python language and basic knowledge of linear algebra for seeking admission in the Applied AI with Deep Learning certification.
Certification Qualification Details
To receive the verified credential, students must complete both the practice quizzes and the final examination in each module of the Applied AI with Deep Learning certification within the time frame specified.
What you will learn
The Applied AI with Deep Learning programme will help the students with
- The candidate will get detailed knowledge of cloud architecture used in artificial intelligence and deep learning concepts.
- The candidates will be exposed to convolutional and recurrent neural networks.
- The candidates will be introduced to the TensorFlow concept with sequential models in Keras.
- The candidates will learn about feedforward food as well as recurrent neural networks.
- With Applied AI with Deep Learning certification syllabus the candidates will advance into concepts of SystemML, Pytorch installation and packages, tensor creation, competition graph and linear models.
- The candidates will use applications in deep learning with anomaly detection, time series forecasting, batch size, auto encoder, image classification and text classification.
- The candidates will learn about scaling and deployment on Apache Spark through Apache SystemML.
The syllabus
Week 1: Introduction to deep learning
Videos
Readings
- IBM Digital Badge
- Video summary on environment setup
- Where to get all the code and slides for download
- Link to Github
Practice Exercise
- DeepLearning Fundamentals
Week 2: Deep Learning Frameworks
Videos
- Introduction to TensorFlow
- Neural Network Debugging with TensorBoard
- Automatic Differentiation
- Introduction video
- Keras overview
- Sequential models in Keras
- Feed forward networks
- Recurrent neural networks
- Beyond sequential models: the functional API
- Saving and loading models
- What is SystemML (1/2)
- What is SystemML (2/2)
- PyTorch Installation
- PyTorch Packages
- Tensor Creation and Visualization of Higher Dimensional Tensors
- Math Computation and Reshape
- Computation Graph, CUDA
- Linear Model
Reading
Link to files in Github
Practice Exercises
- TensorFlow
- TensorFlow 2
- Apache SystemML
- PyTorch Introduction
Week 3: Deep Learning Applications
Videos
- Introduction to Anomaly Detection
- How to implement an anomaly detector (1/2)
- How to implement an anomaly detector (2/2)
- How to deploy a real-time anomaly detector
- Introduction to Time Series Forecasting
- Stateful vs. Stateless LSTMs
- Batch Size
- Number of Time Steps, Epochs, Training and Validation
- Training Set Size
- Input and Output Data Construction
- Designing the LSTM network in Keras
- Anatomy of an LSTM Node
- Number of Parameters
- Training and loading a saved model
- Classifying the MNIST dataset with Convolutional Neural Networks
- Image classification with Imagenet and Resnet
- Autoencoder - understanding Word2Vec
- Text Classification with Word Embeddings
Practice Exercises
- Anomaly Detection
- Sequence Classification with Keras LSTM Network
- Image Classification
- NLP
Week 4: Scaling and Deployment
Videos
- Run Keras Models in Parallel on Apache Spark using Apache SystemML
- Computer Vision with IBM Watson Visual Recognition
- Text Classification with IBM Watson Natural Language Classifier
Readings
- Exercise: Scale a Deep Learning Model on IBM Watson Machine Learning
- Link to Github
Practice Exercise
Methods of parallel neural network training
Admission details
Filling the form
In order to apply, students must complete the steps below for the Applied AI with Deep Learning online programme
Step 1: Students must go to the website mentioned. https://www.coursera.org/learn/ai
Step 2: The students must choose "enrol" from the drop-down menu.
Step 3: The students must then complete the form's qualifications.
Step 4: To gain access to the course content, you must first pay the course fee.
Scholarship Details
Note: Financial aid is available to enrolled students, but the percentage awarded has not been disclosed.
How it helps
The Applied AI with Deep Learning certification benefits the candidates who wish to advance into the areas of machine learning, artificial intelligence and deep learning. The certificate has an exam that has assignments and basic eligibility to enrol and that itself speaks about the quality and level of rigour provided by the coursework for the candidates pursuing the course. The test, which requires a significant amount of time in the form of reading materials and assignments for final certification.
The credential includes a signature and is formally attested by majorly IBM Research-based instructors who are world-renowned experts in this field, When added to the portfolio, the credential has a huge amount of traction in the candidate's profile, allowing him or her to add it to their resume as well as social networking platforms like Linkedin, where they can engage with prospective recruiters and other people interested in pursuing a career in deep learning.
It is easier for recruiters who work in this field to note and shortlist applicants for interviews when the credential is shared in addition to the individual's resume or CV. An applicant who is in the process of seeking several jobs in technical fields would be able to negotiate a good remunerative offer and would also be able to have an advantage over other applicants for a promotion or a shift in the job profile.
Instructors
FAQs
What is the cost of enrolling in the online programme?
There is no charge decided as the Applied AI with Deep Learning fee since the registration and learning of the programme are free. But after 7 days of free trial ends, candidates have to pay Rs. 3583 as fees.
Can I apply for any scholarship or financial aid for pursuing this programme?
Yes, during their Applied AI with Deep Learning training, students would be granted scholarship assistance.
Is there any eligibility for this course?
Yes, the Applied AI with Deep Learning certification will need the candidate to have the expertise as a programmer in Python programming with basic knowledge of linear algebra.
Are subtitles available or included in the certificate course?
Yes, for the benefit of the students' understanding, the course contains subtitles in ten languages, including English.
How can I get admitted or enrol in the course?
In order to register for a course, go to the following website. https://www.coursera.org/learn/ai
When will students be able to view the course materials?
The course guides will be available to students who enrol in the Applied AI with Deep Learning programme curriculum.
Is there a free trial form of enrollment or admission open for Coursera participants?
Yes, students would have access to a specified course during a 7-day free trial duration.
Is it possible to distribute the certificate across different platforms?
Yes, the credential for the Applied AI with Deep Learning online course can be shared on several professional networking and academic platforms.
How long will the coursework take to complete?
The course is 25 hours long and is divided into modules that concentrate on the programme structure and syllabus.
Do students have the option of choosing their own class time or timetable in the course?
Yes, Applied AI with Deep Learning certification benefits the students who need a flexible schedule and deadline for learning.
Articles
Popular Articles
Latest Articles
Similar Courses


Knowledge Based Artificial Intelligence Cognitive ...
Georgia Tech via Udacity


Artificial Intelligence for Robotics
Georgia Tech via Udacity

Secure and Private Artificial Intelligence
Facebook via Udacity


Artificial Intelligence Workflow Artificial Intell...
IBM via Coursera

Developing AI Applications on Azure
LearnQuest via Coursera

Artificial Intelligence
Udacity

Self-Driving Car Engineer
Udacity
Courses of your Interest

TOGAF 9 Combined Level 1 and Level 2 Training
SkillUp Online via Simplilearn

Advanced Certificate Program in DevOps
CMU School of Computer Science, Pitts... via TalentSprint

Mastering Deep Learning Using Apache Spark
Simpliv Learning

Devops with AWS CodePipeline Jenkins and AWS CodeD...
Simpliv Learning

Machine Learning with Python from Linear Models to...
MIT Cambridge via Edx

Big Data Capstone Project
The University of Adelaide, Adelaide via Edx

Advanced Certification Program in Big Data
Belhaven University, Mississippi via Intellipaat

Computer Applications of Artificial Intelligence a...
Purdue University, West Lafayette via Edx
Advanced Power Searching With Google
Google via Edx
More Courses by IBM
Cloud Application Developer Capstone
IBM via Edx
Full Stack Application Development Capstone Projec...
IBM via Coursera
Advanced Data Science Capstone
IBM via Coursera
Advanced Machine Learning and Signal Processing
IBM via Coursera
AI Capstone Project with Deep Learning
IBM via Coursera
Applied Deep Learning Capstone Project
IBM via Edx