AI for Scientific Research - Project Details

Project Description

Completed a 4-course specialization on AI for Scientific Research, covering:

  • Course 1: Python for Data Science and AI, including exploratory data analysis (EDA), machine learning, and linear regression.
  • Course 2: Machine Learning for Scientific Research, covering data preprocessing, SVMs, K-means clustering, random forests, and neural networks.
  • Course 3: Advanced AI Techniques, including neural networks, regularization, and hyper-parameter tuning.
  • Course 4: Capstone Project - Genome Sequencing for COVID-19 Mutations, using PCA, K-means clustering, and TensorFlow for model creation and training.

The skill set required include

  • Technical Skills:
    • Python programming for data science and AI
    • Machine learning (scikit-learn, TensorFlow)
    • Data preprocessing and analysis (NumPy, Pandas)
    • Neural networks and deep learning
    • Genome sequencing and analysis
    • TensorFlow for model creation and training
  • Soft Skills:
    • Self-directed learning and specialization
    • Problem-solving and analytical thinking
    • Programming and coding skills
    • Data analysis and interpretation

MI Dataset Engineering Community Deveopment | Computer Appreciation