Event Details

ICFOSS is organising a 10 day session on “Machine Learning through FOSS” starting from 26th December 2021. 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 traditional class room based trainings. The sessions are scheduled as morning and evening batches.

Objectives:

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 : Introduction to Free software, Machine Learning (Basics, Python Core-Data types, operators, Conditions, Loops, Python Core -List, Tuples, sets, Dictionaries & Functions, NumPy. Pandas & Seaborn, Streamlit Deployment Basics EDA, Heroku deployment, Descriptive Statistics, Sample vs Population statistics,Random Variables, Probability distribution function, Expected value, Binomial Distribution.Normal Distributions, Z-score, Central limit Theorem, Hypothesis testing, Z-Stats vs T-stats, Type 1 type 2 error, Confidence interval, Chi-Square test, ANOVA test, F-stats, Regression with streamlit deployment. Naive-Bayes with Streamlit deployment, Decision Tree with Streamlit deployment, SVM with streamlit deployment, K- means with Streamlit deployment.


• Online examination and project presentation

Participants:

• The number of participants for the proposed programme is limited to 50 per batch.
• Students, Faculty & professionals in the field of Science and Engineering.
• Application shall be invited online. Registration link shall be published through ICFOSS website and social media pages.

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

• 80% of attendance
• 50% marks in Online Examination
• 50% marks in Assignments & Project
• 50% marks on Project Presentation.

Dates: One Batch from Dec 26th 2021 to Jan 29th 2022 only on Weekends from 2.00pm to 5.00pm.

Sl.No	Training Programme	Dates	Time	Course Fee
1	Machine Learning through FOSS	26th Dec 2021 to 29th Jan 2022 (Only on Weekends)	2.00 PM to 5.00 PM	Rs.2,000/-

Registration Fee: Registration fee of Rs.2,000/- shall be charged from each participant.

The registration will be open till Dec 17th 2021.

For online payment, the 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

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

Particulars	Size	Format
Passport Size Photo	20 kb to 40 kb	JPeg, PNG
Signature	10 kb to 30 kb	JPeg, PNG
ID Card	10 kb to 40 kb	JPeg, PNG
Transaction Image	20 kb to 40 kb	JPeg, PNG

Interested persons shall register using the link provided below:

Register here

For more details of the programme, please contact +91 7356610110 | +91 2700012 /13 |+91 471 2413013 | +91 9400225962 | between 10:00-17:00 hrs for any clarifications.