Bioinformatics Specialization
Genome sequencing, disease gene discovery, computational Tree of Life construction, bioinformatics' impact on current biology, computational biology software, and an Honors Track for software programming and algorithm implementation are covered in the course.
Description for Bioinformatics Specialization
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by University of California San Diego
Duration: 3 months at 10 hours a week
Schedule: Flexible
Pricing for Bioinformatics Specialization
Use Cases for Bioinformatics Specialization
FAQs for Bioinformatics Specialization
Reviews for Bioinformatics Specialization
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Bioinformatics Specialization
Learn to leverage Generative AI for automation, software development, and optimizing outputs with Prompt Engineering.
Welcome to the 'Gen AI for Code Generation for Python' course, where you will begin a journey to hone and expand your abilities in the field of code generation using Generative AI.
Learn to use the latest LLM APIs, the LangChain Expression Language (LCEL), and develop a conversational agent.
Master coding basics and create a Hangman game using generative AI tools like Google Bard in a beginner-friendly, 1.5-hour guided project.
Learn about AI principles and platforms like IBM Watson and Hugging Face, integrate RAG technology for chatbot intelligence, create web apps using Python libraries, and develop interfaces with generative AI models and Python frameworks.
Acquire practical skills to build a generative AI application by constructing a retrieval augmented generation (RAG) system using data, Qdrant, and LLMs.
Gain expertise in deploying and managing LLMs on Azure, optimizing interactions with Semantic Kernel, and applying Retrieval Augmented Generation (RAG) techniques.
Gain expertise in deploying and managing LLMs on Azure, optimizing interactions with Semantic Kernel, and applying Retrieval Augmented Generation (RAG) techniques.
Develop applications that are intelligent. In four practical courses, acquire a comprehensive understanding of the fundamentals of machine learning.
Set up for a profession in machine learning. To become job-ready in less than three months, acquire the skills and practical experience that are in high demand.
Featured Tools
Begin Your Professional Journey in Data Engineering. Proficient in the development and execution of data solutions that leverage Microsoft Azure data services.
Explore the differences between ML in Finance and Technology, evaluation methods for regression and classification models, Reinforcement Learning for stock trading, and modeling techniques for market frictions and feedback in option trading.
This course provides learners with the necessary skills to utilize AI tools for innovation, automation, and decision-making, with an emphasis on the principles and applications of AI.
Acquire the skills necessary to program powerful systems in Rust. Through projects in data engineering, Linux tools, DevOps, LLMs, Cloud Computing, and machine learning operations, acquire the skills necessary to develop software that is both efficient and robust, utilizing Rust's distinctive safety and speed.
Prepare for a vocation as a data scientist. Acquire hands-on experience and in-demand skills to become job-ready in as little as five months. No prior experience is necessary.