- Data Science
- Artificial Neural Network
- Artificial Intelligence (AI)
- Machine Learning
- Random Forest
- regression
- Statistical Hypothesis Testing
- medical data
- Python Programming
- PCA
- identifying specieis
- predictions in science
Spécialisation AI for Scientific Research
Lancez votre carrière en science des données. Use artificial intelligence to discover and test hypothesis.
Offert par
Ce que vous allez apprendre
How to use AI in scientific situations to discover trends and patterns within datasets
The complete machine learning process
U​se artificial intelligence to predict sequences in datasets
Employ artificial intelligence techniques to test hypothesis in Python
Compétences que vous acquerrez
À propos de ce Spécialisation
1 722 consultations récentes
In the AI for Scientific Research specialization, we'll learn how to use AI in scientific situations to discover trends and patterns within datasets. Course 1 teaches a little bit about the Python language as it relates to data science. We'll share some existing libraries to help analyze your datasets. By the end of the course, you'll apply a classification model to predict the presence or absence of heart disease from a patient's health data. Course 2 covers the complete machine learning pipeline, from reading in, cleaning, and transforming data to running basic and advanced machine learning algorithms.In the final project, we'll apply our skills to compare different machine learning models in Python. In Course 3, we will build on our knowledge of basic models and explore more advanced AI techniques. We’ll describe the differences between the two techniques and explore how they differ. Then, we’ll complete a project predicting similarity between health patients using random forests. In Course 4, a capstone project course, we'll compare genome sequences of COVID-19 mutations to identify potential areas a drug therapy can look to target. By the end, you'll be well on your way to discovering ways to combat disease with genome sequencing.
Projet d'apprentissage appliqué
E​ach course in this specialization contains practice labs built on the Coursera lab platform. You will use the provided libraries and models to perform machine learning and AI instructions that help answer important questions in your dataset. The final course is a capstone project where you will compare genome sequences of COVID-19 mutations to identify potential areas a drug therapy can look to target. It begins with the basic setup and walks through the entire analysis process.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
Cours en ligne à 100 %
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Planning flexible
Définissez et respectez des dates limites flexibles.
Niveau débutant
There are no specific background requirements; however, it is very helpful to understand scientific methods, mathematics and general computer logic.
Approximativement 4 mois pour terminer
Rythme recommandé de 3 heures/semaine
Anglais
Sous-titres : Anglais
Certificat partageable
Obtenez un Certificat lorsque vous terminez
Cours en ligne à 100 %
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Planning flexible
Définissez et respectez des dates limites flexibles.
Niveau débutant
There are no specific background requirements; however, it is very helpful to understand scientific methods, mathematics and general computer logic.
Approximativement 4 mois pour terminer
Rythme recommandé de 3 heures/semaine
Anglais
Sous-titres : Anglais
Comment fonctionne la Spécialisation
Suivez les cours
Une Spécialisation Coursera est une série de cours axés sur la maîtrise d'une compétence. Pour commencer, inscrivez-vous directement à la Spécialisation ou passez en revue ses cours et choisissez celui par lequel vous souhaitez commencer. Lorsque vous vous abonnez à un cours faisant partie d'une Spécialisation, vous êtes automatiquement abonné(e) à la Spécialisation complète. Il est possible de terminer seulement un cours : vous pouvez suspendre votre formation ou résilier votre abonnement à tout moment. Rendez-vous sur votre tableau de bord d'étudiant pour suivre vos inscriptions aux cours et vos progrès.
Projet pratique
Chaque Spécialisation inclut un projet pratique. Vous devez réussir le(s) projet(s) pour terminer la Spécialisation et obtenir votre Certificat. Si la Spécialisation inclut un cours dédié au projet pratique, vous devrez terminer tous les autres cours avant de pouvoir le commencer.
Obtenir un Certificat
Lorsque vous aurez terminé tous les cours et le projet pratique, vous obtiendrez un Certificat que vous pourrez partager avec des employeurs éventuels et votre réseau professionnel.
Cette Spécialisation compte 4 cours
Introduction to Data Science and scikit-learn in Python
22 évaluations
This course will teach you how to leverage the power of Python and artificial intelligence to create and test hypothesis. We'll start for the ground up, learning some basic Python for data science before diving into some of its richer applications to test our created hypothesis. We'll learn some of the most important libraries for exploratory data analysis (EDA) and machine learning such as Numpy, Pandas, and Sci-kit learn. After learning some of the theory (and math) behind linear regression, we'll go through and full pipeline of reading data, cleaning it, and applying a regression model to estimate the progression of diabetes. By the end of the course, you'll apply a classification model to predict the presence/absence of heart disease from a patient's health data.
Machine Learning Models in Science
This course is aimed at anyone interested in applying machine learning techniques to scientific problems. In this course, we'll learn about the complete machine learning pipeline, from reading in, cleaning, and transforming data to running basic and advanced machine learning algorithms. We'll start with data preprocessing techniques, such as PCA and LDA. Then, we'll dive into the fundamental AI algorithms: SVMs and K-means clustering. Along the way, we'll build our mathematical and programming toolbox to prepare ourselves to work with more complicated models. Finally, we'll explored advanced methods such as random forests and neural networks. Throughout the way, we'll be using medical and astronomical datasets. In the final project, we'll apply our skills to compare different machine learning models in Python.
Neural Networks and Random Forests
In this course, we will build on our knowledge of basic models and explore advanced AI techniques. We’ll start with a deep dive into neural networks, building our knowledge from the ground up by examining the structure and properties. Then we’ll code some simple neural network models and learn to avoid overfitting, regularization, and other hyper-parameter tricks. After a project predicting likelihood of heart disease given health characteristics, we’ll move to random forests. We’ll describe the differences between the two techniques and explore their differing origins in detail. Finally, we’ll complete a project predicting similarity between health patients using random forests.
Capstone Project: Advanced AI for Drug Discovery
In this capstone project course, we'll compare genome sequences of COVID-19 mutations to identify potential areas a drug therapy can look to target. The first step in drug discovery involves identifying target subsequences of theirs genome to target. We'll start by comparing the genomes of virus mutations to look for similarities. Then, we'll perform PCA to cut down our number of dimensions and identify the most common features. Next, we'll use K-means clustering in Python to find the optimal number of groups and trace the lineage of the virus. Finally, we'll predict similarity between the sequences and use this to pick a target subsequence. Throughout the course, each section will consist of a programming assignment coupled with a guide video and helpful hints. By the end, you'll be well on your way to discovering ways to combat disease with genome sequencing.
Offert par
LearnQuest
LearnQuest is the preferred training partner to the world’s leading companies, organizations, and government agencies. Our team boasts 20+ years of experience designing, developing and delivering a full suite industry-leading technology education classes and training solutions across the globe. Our trainers, equipped with expert industry experience and an unparalleled commitment to quality, facilitate classes that are offered in various delivery formats so our clients can obtain the training they need when and where they need it.
Foire Aux Questions
Quelle est la politique de remboursement ?
Puis-je m'inscrire à un seul cours ?
Une aide financière est-elle possible ?
Puis-je suivre le cours gratuitement ?
Ce cours est-il vraiment accessible en ligne à 100 % ? Dois-je assister à certaines activités en personne ?
Quelle est la durée nécessaire pour terminer la Spécialisation ?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
Puis-je obtenir des crédits universitaires si je réussis la Spécialisation ?
What will I be able to do upon completing the Specialization?
D'autres questions ? Visitez le Centre d'Aide pour les Étudiants.
