Molecular Machine Learning Foundation

5

(18 RATINGS)

COHORT-BASED COURSE

NEXT COHORT STARTS IN

Molecular Machine Learning Foundation
NEXT COHORT

Mon, 3rd February, 2025

COURSE DURATION

3 Months

COURSE LEVEL

Beginner

€299.00 one-time payment

For self-paced learning options, contact us

NEXT COHORT
Feb 3-Feb 21, 2025
Every Mon, Wed & Fri, 5-7:30 PM CEST (Berlin)
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HOSTED BY
Pankaj Mishra, PhD

Pankaj Mishra, PhD

Molecular AI Specialist with 13+ Years of Experience | Founder & CTO, Future Therapeutics | Building Proprietary AI Infrastructure for Drug Discovery | Co-founder, Neovarsity

Pre-requisites

You should be familiar with:

Python Programming

About the Course

This course is an ideal starting point for those interested in machine learning for drug discovery but unsure about their abilities. It offers a comprehensive introduction to machine learning principles tailored specifically for small molecule drug discovery applications. By enrolling in this course, you will gain a strong understanding of core concepts and essential techniques in machine learning for drug discovery. We cover key topics such as the molecular machine learning software stack, data collection and preprocessing, molecular feature engineering, model building and quality control. T

Flexible learning options

  • Attend live (virtual) lectures
  • Access recorded lectures in your private dashboard

Practical application

  • Apply your skills through hands-on projects
  • Engage in real-world case studies

Personalized learning experiences

  • Tailored support and guidance
  • 24x7 support by our dedicated support team

Specialized community access

  • To our Members-only Slack community
  • To our invite-only deep tech global Slack community

Syllabus Overview

  • Working with Python Virtual Environments
  • Molecular ML Software Installation (Windows)
  • Molecular ML Software Installation (macOS)
  • Molecular ML Software Installation (Linux)
  • Introduction to Machine Learning in Drug Discovery
  • Molecular ML Software Stack
  • Dataset and Literature
  • Computational Molecular Representations
  • Molecular Data Files Handling & Conversions
  • Molecular Standardization
  • Molecular Descriptors
  • Molecular Diversity Set Selection
  • Molecular Similarity Analysis
Meet your Instructors
Pankaj Mishra, PhD
Pankaj Mishra, PhD
Instructor
Molecular AI Specialist with 13+ Years of Experience
Dr. Pankaj Mishra is the co-founder of Neovarsity, a Berlin-based deep-tech learning venture. He is also the founder of Future Therapeutics, a Berlin-based AI-native therapeutics discovery company that builds and leverages proprietary AI infrastructure to find new cures. He specializes in molecular artificial intelligence and holds a Ph.D. from the University of Freiburg, Germany. He earned his master's degree in pharmaceutical chemistry from the renowned Indian Institute of Technology (BHU), India. During his academic tenure, he co-authored research publications in esteemed journals, including the Journal of Medicinal Chemistry, European Journal of Medicinal Chemistry, Nature Immunology, and Nature Cell Biology.

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What Our Learners Say

My Neovarsity coursework gave me the expertise needed
I have been actively applying my newly acquired skills to the medicinal chemistry projects I am involved in [at Rutgers]. This involved creating targeted libraries and generating various substituents for my lead compounds. Fu
Anastasiia Tsymbal
Anastasiia Tsymbal
Research Associate
Rutgers University, New Jersey, USA
The instructor has done an excellent job!
The instructor has done an excellent job! The course quickly brought me up to speed not only on how to manipulate, prepare, and analyze chemical data but also on how to use them in building machine-learning models for drug di
Fabio Esposito
Fabio Esposito
Research Fellow
Sassari University

Enroll Now

Molecular Machine Learning Foundation
For customised payments options, contact us

03 Feb, 2025

Molecular Machine Learning Foundation
One-Time Payment
€299.00

All taxes included

  • One year complete access
  • Shareable certificate on completion
  • Career guidance from instructors
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Frequently Asked Questions

This course is suitable for individuals who are interested in machine learning in the context of drug discovery. It is designed for learners who may have limited or no prior experience in the field of molecular machine learning but are eager to gain knowledge and skills in this domain. Whether you are a student, researcher, or professional looking to expand your expertise, this course provides a comprehensive introduction and foundation in machine learning principles tailored specifically for small molecule drug discovery applications.


You will have access to the course for 1 year from the date of your registration. Instructor support is available for 3 months from the day of your registration.


The course is designed to be completed within 12-14 weeks. We recommend dedicating at least 6 hours per week to fully benefit from the course content and to ensure adequate practice.


You will retain access to the course materials on your dashboard for 1 year, providing ample time to complete the course at your own pace and request a certificate. We kindly remind you that while we are dedicated to assisting you, active support from instructors and mentors will be available for the first 3 months after your registration. This policy helps us manage our resources effectively and ensures that we can offer the best possible support to all learners.