Online Course – Certified Professional Internship in Artificial Intelligence for Scientific Research by LearnQuest

Launch your career in data science. Use artificial intelligence technologies to discover and test hypotheses.

Suggested by: Coursera (What is Coursera?)

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קורס אונליין - התמחות מקצועית מוסמכת באינטליגנציה מלאכותית למחקר מדעי של LearnQuest

Professional Certificate

Beginners

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Introduction to the Python language and basic models
  • Applying a classification model to predict heart disease
  • Data reading, cleaning and data conversion
  • Running algorithms and machine learning
  • Comparing different models in projects
  • Advanced AI techniques
  • Predicting similarity between health patients using random forests
  • Comparing genome sequences of COVID-19 mutations
  • Using libraries and models in machine learning and artificial intelligence

What you will learn in the course

Courses for which the course is suitable

  • Data Analyst
  • Data Scientist
  • Artificial Intelligence Engineer
  • Healthcare software developer
  • Life sciences researcher
  • Machine Learning Expert
  • Analyzes trends in scientific data
  • Medical predictive model developer
  • Genomics researcher
  • Medical Data Analysis Specialist

Internship – 4-part course series

In the AI ​​for Scientific Research specialization, we will learn how to use artificial intelligence to identify trends and patterns in scientific data.

Courses:

  • Course 1: Introduction to Python and basic models. Implementation of a classification model for predicting heart disease.
  • Course 2: Machine Learning Pipeline – Reading Data, Cleaning and Transforming Data, Running Algorithms. Final Project to Compare Different Models.
  • Course 3: Advanced AI Techniques. A project to predict similarity between healthcare patients using random forests.
  • Course 4: Final Project – Comparing genome sequences of COVID-19 mutations to identify potential regions for drug treatments.

Active Learning Project

Each course includes practice labs on the Coursera Labs platform. You’ll use libraries and models to execute machine learning and artificial intelligence instructions to help answer questions in your data.

Details of the courses that make up the specialization

Data Science and Machine Learning Courses

Course 1: Introduction to Data Science and Skeet-Learn in Python

Duration: 13 hours
Rating: 3.8 (40 ratings)

  • What you will learn: Artificial intelligence techniques to test hypotheses in Python, implementing a machine learning model with NumPy, Pandas, and Scikit-Learn.
  • Skills you will acquire: Data science, machine learning, medical data, regression, statistical hypothesis testing.

Course 2: Machine Learning Models in Science

Duration: 11 hours
Rating: 3.8 (10 ratings)

  • What you will learn: Implementation and evaluation of machine learning models (neural networks, random forests) on scientific data in Python.
  • Skills you will acquire: Random Forest, Artificial Neural Network, Python Programming, Machine Learning, PCA.

Course 3: Neural Networks and Random Forests

Duration: 10 hours

  • What you will learn: In-depth analysis of neural networks and advanced AI techniques.
  • Skills you will acquire: Random forest, artificial neural network, machine learning, predictions in science, species identification.

Course 4: Final Project: Advanced AI for Drug Discovery

Duration: 12 hours

  • What you will learn: Analyze gene sequences to find similarities and identify subsequences using predictive models.
  • Skills you will acquire: Dimensionality reduction, K-Means clustering, whole gene sequences, machine learning, drug discovery.

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