Course Name: Applied Linear Algebra for Signal Processing, Data Analytics and Machine Learning

Course abstract

This course aims to introduce students to all the basic and advanced concepts in Linear Algebra with a strong focus on applications. Linear Algebra is one of the fundamental tools that has applications in diverse fields such as Machine Learning, Data Analytics, Signal Processing, Wireless Communication, Operations Research, Control and Finance. The course is suitable for all UG/PG students and practicing engineers/ scientists/ managers from the diverse fields mentioned above and interested in learning about the novel cutting edge applications of linear algebra in various fields such as Machine Learning, Data Analytics, Signal Processing, Wireless Communication.


Course Instructor

Media Object

Prof. Aditya K. Jagannatham

Prof. Aditya K. Jagannatham (http://home.iitk.ac.in/~adityaj/index.html) received his Bachelors degree from the Indian Institute of Technology, Bombay and M.S. and Ph.D. degrees from the University of California, San Diego, U.S.A.. From April 07 to May 09 he was employed as a senior wireless systems engineer at Qualcomm Inc., San Diego, California, where he worked on developing 3G UMTS/WCDMA/HSDPA mobile chipsets as part of the Qualcomm CDMA technologies division. His research interests are in the area of next-generation wireless communications and networking, sensor and ad-hoc networks, digital video processing for wireless systems, wireless 3G/4G cellular standards and CDMA/OFDM/MIMO wireless technologies. He has contributed to the 802.11n high throughput wireless LAN standard and has published extensively in leading international journals and conferences. He was awarded the CAL(IT)2 fellowship for pursuing graduate studies at the University of California San Diego and in 2009 he received the Upendra Patel Achievement Award for his efforts towards developing HSDPA/HSUPA/HSPA+ WCDMA technologies at Qualcomm. Since 2009 he has been a faculty member in the Electrical Engineering department at IIT Kanpur, where he is currently an Associate Professor, and is also associated with the BSNL-IITK Telecom Center of Excellence (BITCOE). At IIT Kanpur he has been awarded the P.K. Kelkar Young Faculty Research Fellowship (June 2012 to May 2015) for excellence in research. His popular video lectures for the NPTEL (National Programme on Technology Enhanced Learning) course on Advanced 3G and 4G Wireless Mobile Communications can found at the following YouTube link ( NPTEL 3G/4G ).
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Teaching Assistant(s)

No teaching assistant data available for this course yet
 Course Duration : Jan-Apr 2021

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 Syllabus

 Enrollment : 18-Nov-2020 to 25-Jan-2021

 Exam registration : 15-Jan-2021 to 12-Mar-2021

 Exam Date : 25-Apr-2021

Enrolled

3060

Registered

174

Certificate Eligible

118

Certified Category Count

Gold

38

Silver

55

Elite

16

Successfully completed

9

Participation

2

Success

Elite

Silver

Gold





Legend

AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75 AND FINAL SCORE >=40
BASED ON THE FINAL SCORE, Certificate criteria will be as below:
>=90 - Elite + Gold
75-89 -Elite + Silver
>=60 - Elite
40-59 - Successfully Completed

Final Score Calculation Logic

  • Assignment Score = Average of best 8 out of 12 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
Applied Linear Algebra for Signal Processing, Data Analytics and Machine Learning - Toppers list
Top 1 % of Certified Candidates

PRASHANT BARTAKKE 100%

COLLEGE OF ENGINEERING PUNE

SUSHMITHA SHREE S 100%

Indian Institute of Technology, Madras


Top 2 % of Certified Candidates

Top 5 % of Certified Candidates

RENISH ISRAEL I 99%

Indian Institute of Technology , Madras .

DR FAYAZUR RAHAMAN MOHAMMAD 99%

MAHATMA GANDHI INSTITUTE OF TECHNOLOGY

M HARI PRASAD 98%

BHARAT ELECTRONICS LTD

LALITHA NAGAPURI 98%

NATIONAL INSTITUTE OF TECHNOLOGY ANDHRA PRADESH

Enrollment Statistics

Total Enrollment: 3060

Registration Statistics

Total Registration : 174

Assignment Statistics




Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.