C12 Advanced ⏱ 5 Weeks 🎯 25 hours 📡 10 live sessions

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Machine Learning for Bioinformatics II

Train models on genomes. Interpret them with biology.

Galaxy for workflows, scikit-learn for classical ML, TensorFlow for deep learning, SHAP for biological interpretation. This course makes you dangerous — you will build models that classify cancer subtypes and predict splice sites from DNA sequences.

Enrol Now → View Curriculum

₦38,000 ≈ $46

Curriculum

What you will learn

Every session is hands-on. Every topic comes with practical exercises using real biological datasets.

Week 1

Galaxy Workflow Platform

Galaxy architecture: histories, datasets, tools, collections, provenance
Building reusable workflows: inputs, outputs, tool parameters
Galaxy RNA-seq pipeline: FastQC → HISAT2 → featureCounts → DESeq2
Publishing and sharing workflows via Galaxy Training Network

Weeks 2–3

Classical Machine Learning for Omics

Handling biological data: imbalance, high-dimensionality, batch effects
Random Forest for cancer subtype classification from gene expression
SVM for protein function prediction from sequence features
Model selection: nested CV, GridSearchCV, calibration curves

Week 4

Dimensionality Reduction & Visualisation

PCA: variance decomposition, scree plot, biplot — for expression data
t-SNE: perplexity, single-cell RNA-seq cell type visualisation
UMAP: large-scale omics embedding, parameter tuning
Combining dimensionality reduction with clustering (Leiden, k-means)

Week 5

Deep Learning for Genomics

CNN architecture: one-hot encoding, convolutional layers, motif detection
TensorFlow/Keras: building, training, evaluating genomic sequence models
LSTM for sequential biological data: splice site, secondary structure
SHAP values: explaining predictions — which features drove the model?

Outcomes

What you will be able to do

Concrete, measurable skills you will take away and use immediately in your research or career.

✓Build and publish a complete bioinformatics workflow in Galaxy
✓Train and evaluate a Random Forest classifier on cancer gene expression data
✓Build a CNN in TensorFlow to classify DNA splice sites from sequence
✓Apply SHAP to explain ML model predictions in biologically meaningful terms

Tools & Software

Galaxyscikit-learnTensorFlow 2 / KerasPyTorchUMAPSHAPJupyter LabpandasNumPy

Course Details

Everything included

One payment — full access to all course materials, live sessions, and community.

What's included

10 live sessions
25 hours content
Jupyter notebooks for all models
CNN training scripts
Galaxy workflow files
Course certificate
Community access
Lifetime recordings

Who this course is for

Bioinformaticians · Data scientists working on omics · Computational biologists entering AI/ML · Genomics researchers using ML tools

Prerequisites

C06 (Python essential). C08 recommended. Basic ML familiarity helpful but not required.

Instructor

Your instructor

Dr. Ashraf Akintola

PhD Biomedical Convergence Science and Technology | Bioinformatics Researcher & Educator

With close to a decade of research experience in genomics and computational biology, Dr. Noble has trained researchers across 40+ countries. His hands-on teaching philosophy has made noblekinbio one of Africa's leading bioinformatics education platforms.

What students say

Trusted by researchers worldwide

Students from 40+ countries have transformed their careers with noblekinbio courses.

"This program changed how I do research. I went from copy-pasting BLAST results to writing my own pipelines. The hands-on approach is unlike any other bioinformatics course I have taken."

Chioma Okonkwo

PhD Student, University of Lagos

"Dr. Noble explains complex algorithms in a way that finally clicks. I completed C04 and C05 and immediately applied them to our malaria genomics project."

Emmanuel Asante

Bioinformatics Analyst, Ghana Health Service

"I was sceptical about an online course being truly hands-on. I was wrong. Every session I was actually running code, not just watching. The Snakemake module alone was worth it."

Fatima Al-Rashidi

Molecular Biology Researcher, Jordan

"C10 gave me the drug discovery computational skills I needed to transition from wet lab to computational research. I have already applied QSAR modelling in my current role."

Oluwaseun Adeyemi

Pharmaceutical Scientist, Nigeria

FAQ

Common questions

How does this work with Selar? +

After clicking "Enrol Now", you will be taken to our Selar checkout page. Pay securely with card, bank transfer, or Flutterwave. Once payment is confirmed, you immediately receive access to the course content and are added to our private student community.

Do I need to attend live sessions? +

Live sessions are strongly recommended for Q&A and community, but all sessions are recorded and available in your Selar account within 24 hours. You have lifetime access to all recordings.

What if the course is not right for me? +

We offer a 7-day refund policy. If you have attended fewer than 2 sessions and completed fewer than 20% of the course, contact us at support@noblekinbio.com for a full refund.

Can I take courses in any order? +

Some courses have prerequisites (shown above). We recommend following the program sequence, but motivated students can discuss exceptions with the instructor via the community.

Is there a group discount? +

Yes — teams of 3+ receive 20% off. Contact us at enrol@noblekinbio.com with your team details.

Will I receive a certificate? +

Yes. Upon completing all assessments, you receive a digital certificate from noblekinbio.com. Completing all 13 courses earns the full Bioinformatics Certificate Program credential.

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Ready to start C12?

Train models on genomes. Interpret them with biology. Enrol today and get instant access to all course materials.

₦38,000 | $46 USD

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