Dr. Omics Education;

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Crash Courses

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Course Requirements

Interest in Learning: Willingness to explore and understand machine learning concepts.
Basic Knowledge: Some background in biology, statistics, and math is helpful.
Tech Curiosity: Interest in applying machine learning to biological data.
Software: Free tools like Python and Jupyter Notebook will be used — no need to buy anything.
Hardware: Laptop or computer with at least 4GB RAM and 100GB storage.
Internet: A good internet connection for using online tools like Google Colab.

Course Description

Learn the Fundamentals – Understand core machine learning concepts, tailored for bioinformatics and life sciences.
Explore Key Algorithms – Gain hands-on experience with linear models, SVM, Naive Bayes, Random Forest, logistic regression, and clustering.
Master Probabilistic Models – Dive into the basics of probabilistic machine learning and how uncertainty is handled in biological data.
Validate Your Models – Learn essential techniques to assess and improve the performance of your machine learning models.

Apply ML to Real-World Problems – Explore machine learning in image analysis and bioinformatics, bridging theory and practical application.

Course Outcomes

Understand key machine learning concepts and their relevance to bioinformatics and life science data analysis.
Implement major ML algorithms such as SVM, Naive Bayes, Decision Trees, Random Forests, and Logistic Regression using real datasets.
Apply clustering and probabilistic models to explore patterns and make data-driven predictions.
Evaluate and validate models using standard performance metrics and validation techniques.
Use machine learning tools like Python, scikit-learn, and Jupyter Notebook to build, test, and deploy ML solutions.

Rules & Regulations

Attendance and Participation: Maintain a minimum of 75% attendance. Regular assessments and attendance contribute to performance evaluation.
Discipline: Maintain punctuality and respect in live classes. Engage actively and interact respectfully with instructors and peers.
Course Fee Payment: Pay course fees on time to avoid suspension or cancellation of access.
Assignments and Project: Complete assignments and projects sincerely and submit them on time.
Feedback and Communication: Maintain open communication with instructors and provide constructive feedback.
Certification: A certificate will be awarded upon course completion.

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