Training AI/ML & systems biology

Building Machine Learning Models for Normal vs. Cancer Classification

A two-week live program on building machine learning models that classify normal and cancer samples from RNA-seq gene expression data, from count matrix to prediction on new data.

  • 2 weeksMon–Fri, live online
  • 1 houra day, evening IST
  • 7 modulesR and Python

Next cohort

Dates to be announced

  • Duration2 weeks
  • ScheduleMon–Fri · 1 hour a day
  • ModeLive online (Google Meet)

Curriculum

Turn transcriptomics data into predictive cancer models

Seven modules working with real datasets throughout.

R / RStudioDESeq2GEO / NCBIPythonJupyterPandasNumPyscikit-learnXGBoostOptunaMatplotlibJoblib

01

RNA-seq and transcriptomic data

Introduction to RNA-seq and transcriptomic datasets. Tool: GEO / NCBI.

02

From count matrix to DEG analysis

Preprocess counts and find differentially expressed genes. Tools: R, DESeq2.

03

Building the ML dataset

Select features and construct a dataset for modeling. Tools: Python, Pandas, NumPy.

04

Model development

Train machine learning classifiers. Tools: scikit-learn, XGBoost.

05

Model optimization

Tune model hyperparameters. Tool: Optuna.

06

Model evaluation and interpretation

Evaluate performance and interpret results. Tool: Matplotlib.

07

Prediction on new data

Save models and classify new samples. Tool: Joblib.

Who should apply

Eligibility

  • Students in B.Sc., B.Tech., M.Sc., M.Tech., B.Pharm, M.Pharm or PhD programs in life sciences, pharmacy or computer science
  • Postdocs and research scholars
  • Teaching and industry professionals

What’s included

Program benefits

  • Live, instructor-led sessions
  • Recordings of every session
  • Workshop materials
  • Certificate
  • Online technical support after the workshop

Fees

Course fees

One fee covers all live sessions, recordings, materials and the certificate. Payment and registration open when the next cohort is announced.

CategoryIndia (INR)International (USD)
Students (up to Master’s)₹2,250USD 40
PhD scholars₹2,500USD 45
Postdocs / research scholars₹2,750USD 50
Staff / faculty₹3,000USD 55
Industry professionals₹3,500USD 60
Fees for the next cohort. USD fees apply to anyone living, working or studying outside India.

Teaching team

Course instructors

AADr. Ajitha AntonyBioinformatics Trainer, CBIRT

TADr. Tamanna AnwarFounder, CBIRT

Format

How the course runs

  • DatesTo be announced
  • SessionsMon–Fri, 1 hour a day (last cohort: 6:00–7:00 PM IST)
  • PlatformGoogle Meet (live)
  • Missed a session?Recordings provided

FAQ

Course questions

When does the next cohort start?

Dates are not announced yet. Click Notify me or message us on WhatsApp, and we’ll tell you when enrollment opens.

Do I need prior experience?

A basic understanding of bioinformatics and transcriptomics is expected.

What will I need on my computer?

A computer running Windows 10/11, macOS or Linux, with at least 8 GB RAM (16 GB recommended), an Intel Core i5 / AMD Ryzen 5 processor or better, and a reliable internet connection.

What if I miss a live session?

Every session is recorded, and you get access to the recordings.

Will I get a certificate?

Yes. The certificate is awarded on completing the course assignment.

Interested in ML Model Building for Cancer Classification?

Get notified when the next cohort opens, or ask us about prerequisites and fees.

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