Machine Learning through FOSS Phase II

Machine Learning
Event Start Date & Time
2020-12-21 10:00:00 AM
Event End Date & TIme
2021-01-02 05:00:00 PM

ICFOSS is organising a 10 day session on Machine Learning through FOSS starting from 21st December 2020. The proposed Certification Programme is a drive to improve the technical capabilities of upcoming engineers towards Free and Open Source Technology. Considering the current Covid pandemic, ICFOSS proposes to conduct Certification Programmes through online, instead of a traditional class room based trainings. The sessions are scheduled as morning and evening batches.

Machine Learning



The Certification Programme shall mainly focus to enhance the skills in Machine Learning (ML) through free software among the participants and in turn, nurture the interest in free software tools. This Online Certification Programme shall be a 10 day-long course which provides the participants with hands on experience on Machine Learning Techniques and Features. The programme also helps them to build creativity and problem-solving skills, in the field of Engineering Technology and Scientific Research. Under the guidance of experienced resource persons from ICFOSS, each participant shall get live online support throughout the course, to complete the tasks assigned to them. The level of progress of each participant will be analysed through simulation tests at the end of each session and a product presentation at the end of the program.

Course Highlights:

  • Online learning

  • Live Virtual Classroom

  • Projects

  • Custom Learning Path

  • Simulation Tests

  • Certification

The Machine Learning (ML) Certification Programme is designed to give the participants with an in-depth knowledge of Machine Learning (ML) Framework in Linux platform. In this hands-on course, the participants will execute projects using integrated lab.

Key Training features:

  • 30 hours of Industry-Lead Training

  • Topics covered : Training on Linux basics, introduction to Free software, Machine Learning (Basics, Pre-processing and Feature engineering, Python Libraries, Regression, Linear models for classification, Artificial Neural Network, Network - Feed Forward, Clustering, SVM, Performance metrics, Recent advances in ML)

  • Online examination and project presentation



  • The number of participants for the proposed programme is limited to 50 per batch.

  • Students , Faculty & Professionals in the field of Sciences and Engineering.

  • Application shall be invited online. Registration link shall be published through ICFOSS website and social media pages.


Selection Criteria: The Selection will be through screening and scrutiny of application, though a Panel of Members, and shortlisted through criteria defined by the Committee of Internal Technical Heads (ITH), ICFOSS.

 Certification Criteria: Certification will be issued to participants who qualifies with:

  • 50% marks in Online Examination

  • 25% marks in Assignments & Projects

  • 25% marks on Project Presentation.


Note: Each project shall be evaluated by a Committee constituted by the ITH. Examination is time bound. Random questions will be generated from the question bank prepared by an expert panel and certified by ITH.


Dates: Multiple batches are available from Dec 21 onwards.

(Morning batch- 3 hours/day from 02.00 PM to 05.00 PM)

(Evening batch- 3 hours/day from 06.00 PM to 09.00 PM )


Registration Fee: Registration fee of Rs. 1,999 /- and Rs. 2,499 shall be charged for Morning & Evening batches.


Interested persons shall register using online form provided below.

For online payment bank accounts details of ICFOSS is as follows:

Account Name : ICFOSS
Account Number : 67242303296
IFSC - SBIN0070737
Name of Bank : State Bank of India
Branch : Technopark, Thejaswini, Thiruvananthapuram

Feel free to contact us at +91 7356610110 during office hours (10.00-17:00 hrs) for any clarifications.

For Registration :

Candidates are requested to upload the below given particulars in the following size & format while registering:





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