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Bioinformatics, Data Analysis & AI
New
104 students
Bioinformatics, Data Analysis & AI
Master genomic sequencing, RNA-seq, machine learning, and 1D CNNs with 60 exam-ready practice questions, 26 interactive
Created byFiada Mothapo
Last updated 9/2026
English
What you'll learn
- Clean, wrangle, and analyze real biological and clinical datasets using Python, pandas, and core statistical methods
- Build a working sequence alignment and variant-calling pipeline using BLAST, BWA, and samtools on real genomic data
- Use AI tools responsibly in scientific work — verifying outputs and catching hallucinated citations or subtly wrong code.
- Train and validate machine learning and deep learning models on gene expression and DNA sequence data without overfitting.
Explore related topics
Included in This Course
60 questions
Description
Bridge the gap between biological science, data analysis, and artificial intelligence with this comprehensive, practical bioinformatics masterclass. Designed for students, researchers, laboratory professionals, life-science graduates, and aspiring bioinformaticians, this course develops practical skills for working with biological and genomic data using Python, statistics, machine learning, deep learning, and generative AI.
You will progress from Python fundamentals and scientific data wrangling to exploratory data analysis, biology and genomics, sequence analysis, alignment workflows, genomic and multi-omics analysis, machine learning, deep learning, and AI applications in bioinformatics.
The course includes 26 interactive Python coding exercises, 60 practice exam questions across two full-length tests, section-based learning, assessments, and a capstone project designed to help you apply your knowledge to a realistic bioinformatics workflow. You will also develop portfolio-ready work and strengthen your ability to approach computational biology problems systematically.
Whether you are preparing for technical interviews, academic assessments, career development, or further study, this course provides a structured pathway from foundational concepts to advanced computational approaches.
Build confidence in Python, analyse biological data, explore modern AI methods, and develop practical bioinformatics skills you can apply to research, laboratory, academic, and professional environments. Develop skills that connect laboratory knowledge with modern computational research and innovation.
Who this course is for:
- \- Bioinformaticians & Computational Biologists preparing for industry technical assessments or certification exams. - Life Scientists & Wet-Lab Researchers looking to master data wrangling, RNA-seq differential expression, and statistical hypothesis testing in Python. - Data Scientists & Machine Learning Engineers transitioning into biotechnology, genomics, or healthcare AI applications. - Students & Graduates seeking to build a reproducible, portfolio-ready Capstone project to showcase to prospective employers.