Introduction to AI & ML techniques in Drug Discovery
Introduction to AI & ML techniques in Drug Discovery, available at $39.99, has an average rating of 3.8, with 13 lectures, based on 131 reviews, and has 733 subscribers.
You will learn about Introduction to drug discovery and applications of AI & ML techniques at different stages ABCDs of AI & ML terminology Introduction to types of Artificial Intelligence & Machine learning Introduction to Neural networks and Natural Language processing Introduction to potential of AI & ML in Drug Discovery Introduction to advantages and limitations of applying AI in drug discovery Current Solution 1: AI based information aggregation from vast literature Current Solution 2: AI based systems modelling to understand disease mechanisms Current Solution 3: AI based systems modelling of novel drug like molecules This course is ideal for individuals who are Bachelors or Masters degree or PhD scholar of Pharmaceutical sciences, Biochemistry, Biotechnology, Chemistry or related who are into drug discovery research will benefit most of this course. It is particularly useful for Bachelors or Masters degree or PhD scholar of Pharmaceutical sciences, Biochemistry, Biotechnology, Chemistry or related who are into drug discovery research will benefit most of this course.
Enroll now: Introduction to AI & ML techniques in Drug Discovery
Summary
Title: Introduction to AI & ML techniques in Drug Discovery
Price: $39.99
Average Rating: 3.8
Number of Lectures: 13
Number of Published Lectures: 13
Number of Curriculum Items: 13
Number of Published Curriculum Objects: 13
Original Price: $44.99
Quality Status: approved
Status: Live
What You Will Learn
- Introduction to drug discovery and applications of AI & ML techniques at different stages
- ABCDs of AI & ML terminology
- Introduction to types of Artificial Intelligence & Machine learning
- Introduction to Neural networks and Natural Language processing
- Introduction to potential of AI & ML in Drug Discovery
- Introduction to advantages and limitations of applying AI in drug discovery
- Current Solution 1: AI based information aggregation from vast literature
- Current Solution 2: AI based systems modelling to understand disease mechanisms
- Current Solution 3: AI based systems modelling of novel drug like molecules
Who Should Attend
- Bachelors or Masters degree or PhD scholar of Pharmaceutical sciences, Biochemistry, Biotechnology, Chemistry or related who are into drug discovery research will benefit most of this course.
Target Audiences
- Bachelors or Masters degree or PhD scholar of Pharmaceutical sciences, Biochemistry, Biotechnology, Chemistry or related who are into drug discovery research will benefit most of this course.
A perfect course for Bachelors / Masters / PhD students who are getting started into Drug Discovery research. This course is specially designed keeping in view of beginner level knowledge on Artificial Intelligence, Machine learning and computational drug discovery applications for science students. By the end of this course participants will be equipped with the basic knowledge required to navigate their drug discovery project making use of the Artificial Intelligence and Machine learning based tools.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction to drug discovery and applications of AI & ML at different stages
Chapter 2: ABCDs of Artificial Intelligence & Machine Learning terminology
Lecture 1: ABCDs of Artificial Intelligence & Machine Learning terminology
Chapter 3: Types of Machine learning
Lecture 1: Types of Machine learning
Chapter 4: Types of Artificial Intelligence
Lecture 1: Types of Artificial Intelligence
Chapter 5: Introduction to Artificial Neural Networks & their applications in DrugDiscovery
Lecture 1: Introduction to Artificial Neural Networks & their applications in DrugDiscovery
Chapter 6: Introduction to Natural Language processing
Lecture 1: Introduction to Natural Language processing & its applications in drug discovery
Chapter 7: Potential & Drawbacks of AI in Drug Discovery
Lecture 1: Potential & Drawbacks of applying Artificial Intelligence in Drug Discovery
Chapter 8: Thirst areas of research where AI & ML are making difference
Lecture 1: Thirst areas of drug discovery research where AI & ML making difference
Chapter 9: Current available solutions in Drug Discovery based on AI and ML techniques
Lecture 1: Artificial Intelligence based information aggregation from vast literature
Lecture 2: Introduction to UNSILO, Penelope, Statcheck, Statreviewer tools
Lecture 3: Artificial Intelligence based article / book writer
Lecture 4: Artificial Intelligence based disease modeling
Lecture 5: Artificial Intelligence based disease designing
Instructors
-
Hussain Basha Syed
Computational Biologist / Chemist
Rating Distribution
- 1 stars: 10 votes
- 2 stars: 12 votes
- 3 stars: 44 votes
- 4 stars: 33 votes
- 5 stars: 32 votes
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