Machine Learning 101
Completed by Abhiram Nimbalkar on August 14, 2025
Verified learner ·
Badge ID: PFzgEVFpT6Oc4BFRaS-jFw
About this Badge
Build and train ML models using NumPy, scikit-learn, and TensorFlow for classification, prediction, decision trees, clustering, anomaly detection, and recommender systems while applying best practices in ML development.
Learning objectives
- Build and train supervised machine learning models using Python libraries such as NumPy and scikit-learn for tasks like linear and logistic regression.
- Develop and implement machine learning models and pipelines on Google Cloud, utilizing AI foundations and tools for data-to-AI lifecycle management.
- Apply machine learning techniques, including supervised and unsupervised learning, to solve real-world problems and enhance AI applications.
Skills learned
- Artificial Intelligence and Machine Learning (AI/ML)
- Natural Language Processing
- Google Cloud Platform
- Generative AI
- Artificial Intelligence
- Predictive Modeling
- Supervised Learning
- Python Programming
- Cloud Infrastructure
- Unsupervised Learning
- Image Analysis
- Regression Analysis
- Feature Engineering
- Statistical Modeling
- Machine Learning
- Cloud Solutions
- Algorithms
- Jupyter
- NumPy
- Data Storage
- Automation
- Scikit Learn (Machine Learning Library)
- Classification And Regression Tree (CART)
- Data-Driven Decision-Making
- Application Programming Interface (API)
Learning content completed
Some of the content and skills presented have been contributed by the content provider.