SciMedian Pvt. Ltd. is a blend of online and onsite education and training in an affordable, flexible, and accessible way. Our growing list of courses aims to empower biomedical graduates to take on truly impactful careers while impacting human lives.
SciMedian Courses
Comprehensive modules in Programming, Machine Learning, Image Analysis, Genomics Data Science, Advanced Statistics and Health Data Analytics
Practical and Hands-On Learning with Industry-Relevant and Real-world data
Unique Features:
- Experienced global educators with Academic and Industry Background
- Networking Opportunities with Industries
- Flexible Learning Options
- Full placement support
Introduction to courses
Health Data Science
Expert Tracks
SciMedian offers expert track courses designed to provide a comprehensive learning experience. With a duration of 6 months plus an additional 4 months for job readiness, these courses not only focus on technical skills but also emphasize personality development, interview preparation, and HR invitations from top campuses. Students receive extensive training until they secure a placement, and gain valuable industry exposure through internships and real-world industry projects.
The Health Data Science course focuses on applying data science techniques to analyze large-scale health-related datasets. It covers topics such as artificial inteligence, machine learning in health science, advanced statistical analysisis, health data handling. Through hands-on exercises and real-world case studies, students gain practical skills to extract meaningful insights for evidence-based decision-making. The course includes lectures, programming exercises, and projects using real healthcare datasets, utilizing tools like R or Python. Upon completion of the course, students will be proficient in analyzing health data and contributing to data-driven decision-making in healthcare organizations.
A clinical research course provides in-depth knowledge and skills for designing, conducting, and analyzing clinical research studies. It covers various topics such as clinical trial management, regulatory affairs, AI in clinical research, data management, and drug development. The course includes lectures, discussions, practical exercises, and assignments, allowing students to gain hands-on experience in data analysis and research article appraisal. By the end of the course, students will possess the necessary skills to contribute effectively to clinical research projects and understand the complexities and ethical challenges involved.
Advanced and short courses
SciMedian come up with short courses that span a few weeks, specifically designed for specialization in various biomedical fields. These courses aim to equip participants with the expertise needed to become industry experts in their chosen field.
Genomic Data Science
Learn to integrate genomics, data analysis, and computational methods to gain deeper insights into genomic data. Apply statistical and computational approaches to interpret large-scale genomic datasets.
Advanced Data Science
Acquire advanced data analytic skills including artificial intelligence to extract meaningful insights from complex and large-scale health datasets, driving innovation and informed decision-making in healthcare.
Clinical Data Sciences
Receive hands-on experience in using electronic health records, large multimodal clinical data, revolutionising medical research, drug discovery and treatment decisions.
Python for Health Data Science with Biopython
Enhance skills in using Python programming for health data science applications, with a focus on the Biopython module. Participants will learn the fundamentals of Python programming and explore its practical applications in analyzing and manipulating biological and health data.
R Programming for Health Data Science with Bioconductor
Build up essential skills to use R programming for health data science applications, with a specific focus on mastering Bioconductor packages. Participants will learn the fundamentals of R programming and explore its practical applications in analyzing and interpreting health-related data.
Clinical Data Management Fundamentals
Achieve fundamentals of clinical data management. Learn key principles and best practices for clinical data analysis and its applications in healthcare through essential topics such as data collection, database design, data validation, quality control, and data cleaning.
RNA-Seq Data Analysis
Gain essential knowledge and skills to effectively analyze RNA-Seq data and extract meaningful insights. Participants will learn the fundamentals of RNA-Seq data analysis.
Onco-Genomics Data Analysis
Attain cutting-edge skills and knowledge to analyze and interpret genomics data in the field of oncology. Learn using onco-genomics for diagnostics and treatment decisions.