Mastering Deep Learning

By Naveen Kumar Bhansali | Indian Institute of Management Bangalore (IIMB)

Learners enrolled: 1905

"Overview: This course offers a comprehensive understanding of Artificial

Neural Networks, Convolutional Neural Networks, and Deep

Learning. It starts with a deep dive into the fundamental principles

of Artificial Neural Networks, including neuron operations and

problem-solving applications. Following this, the course explores

Convolutional Neural Networks, emphasizing their use in

computer vision, explaining convolutional and pooling layers, and

their impact on image classification.

Objectives: Understand the fundamental principles of Artificial Neural

Networks (ANNs) and their applications in solving complex

problems

• Apply ANNs to solve complex problems, utilizing

appropriate frameworks and programming

• languages, such as TensorFlow or PyTorch, to build and train

neural networks

• Demonstrate the acquired knowledge and skills to develop

practical solutions using ANNs and CNNsfor complex

problems in diverse domains

• Implement and evaluate the performance of CNNs in image

recognition, object detection, and other computer vision

applications

• Analyze the architectural components of Convolutional

Neural Networks (CNNs) and their role in computer vision

tasks

• Construct cutting-edge solutions by applying Artificial

Neural Networks, Convolutional Neural Networks to solve

complex real-world problems across diverse domains."

Summary

Course Status :	Completed
Course Type :	Core
Language for course content :	English
Duration :	6 weeks
Category :	Management Studies
Credit Points :	3
Level :	Postgraduate
Start Date :	26 Jul 2024
End Date :	31 Oct 2024
Enrollment Ends :	31 Aug 2024
Exam Date :	07 Dec 2024 IST
Shift :	1

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1: Introduction to ANN and Deep Learning
Week 2: Neural Networks, Hyperparameter and Model Building
Week 3: Optimizers, Model Regularization and Auto Encoding
Week 4: Deep Learning and Convolutional Neural Network
Week 5: CNN Architecture and Transfer Learning

Syllabus Page

Exam Schedule

Books and references

"Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, Third

Edition and other reference shared in seprate document"

Instructor bio

Naveen Kumar Bhansali

Indian Institute of Management Bangalore (IIMB)

"Naveen Kumar Bhansali is a distinguished professional who holds

multiple key roles in the field of artificial intelligence, data science

and big data. He is not only the Co-founder and CTO of BlitzAI, but

also an adjunct faculty at IIM Bangalore, with multiple decades of

experience as AI advisory consultant, big data solution architect,

and data scientist for clients in diverse industries globally,

including finance, insurance, healthcare, telecom, retail, FMCG, e-

commerce, and IT-Exchange and Storage.

In addition to his extensive industry experience, he is also an

active contributor to the analytics community in India. He

currently serves as the Vice President of the Analytical Society of

India, which is the first and largest body of analytics professionals

and organisations in the country. Furthermore, he has earned the

Chartered Financial Analyst (CFA) level 2 certification, showcasing

his expertise in the field of finance.

Apart from his professional roles, he is also the Director of R&N

Capital Market Pvt. Ltd., a company specialising in stock broking

and capital market analysis. His multifaceted background and

diverse skill set make him a highly respected and accomplished

professional in the field of artificial intelligence, data science, and

finance."

Course certificate

Enrolling and learning from the course is free. However, if you wish to obtain a certificate, you must register and take the proctored exam in person at one of the designated exam centre’s. The registration URL will be announced when the registration form is open. To obtain the certification, you need to fill out the online registration form and pay the exam fee. More details will be provided when the exam registration form is published, including any potential changes. For further information on the exam locations and the conditions associated with filling out the form, please refer to the form.

Grading Policy:

Assessment Type	Weightage
Mid-Term & End-Term	25%
Final Exam	75%

Certificate Eligibility:

40% marks and above in internal assessment (Mid Term & End Term)
40% marks and above in the final proctored exam

Score	Type of Certificate
>=90	Gold
75 - 89	Silver
70 - 74	Bronze
40 - 70	Successfully Completed
<40	No Certificate

Sample Certificate:

Disclaimer: In order to be eligible for the certificate, you must register for enrolment and exams using the same email ID. If different email IDs are used, you will not be considered eligible for the certificate.

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