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  • Skills you'll gain: Model Evaluation, Unsupervised Learning, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Machine Learning Methods, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Predictive Modeling, Random Forest Algorithm, Decision Tree Learning, Model Optimization, Logistic Regression, Classification Algorithms

  • Skills you'll gain: Feature Engineering, Model Evaluation, Machine Learning Algorithms, Model Optimization, Machine Learning Methods, Random Forest Algorithm, Advanced Analytics, Algorithms, Applied Machine Learning, Decision Tree Learning, Predictive Modeling, Data Preprocessing, Fine-tuning, Performance Tuning

  • Skills you'll gain: Model Optimization, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Machine Learning Software, Model Training, Data Preprocessing, Data Processing, Hugging Face, Classification Algorithms

  • Skills you'll gain: Computer Vision, Model Evaluation, Supervised Learning, Image Analysis, Data Preprocessing, Applied Machine Learning, Machine Learning Methods, Feature Engineering, Machine Learning Algorithms, Data Processing, Model Training, Model Optimization, Machine Learning, Data Cleansing, Scikit Learn (Machine Learning Library), Machine Learning Software, Data Integration, Data Transformation, Classification Algorithms, Dimensionality Reduction

  • Skills you'll gain: Supervised Learning, Model Optimization, Feature Engineering, Applied Machine Learning, Unsupervised Learning, Model Evaluation, Machine Learning Methods, Statistical Machine Learning, Machine Learning Algorithms, Predictive Modeling, Model Training, Data Preprocessing, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Data Transformation, Fine-tuning

  • Skills you'll gain: Model Training, Model Evaluation, Data Preprocessing, Machine Learning Methods, Statistical Methods, Statistical Machine Learning, Data Validation, Data Quality, Mathematical Software, Classification Algorithms, Machine Learning Algorithms

What brings you to Coursera today?

  • Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Model Training, Random Forest Algorithm, Model Optimization, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms

  • Skills you'll gain: Generative AI, Generative Model Architectures, Generative Adversarial Networks (GANs), Responsible AI, Applied Machine Learning, Data Ethics, Transfer Learning, Artificial Intelligence, Model Optimization, Federated Learning, Machine Learning Methods, Scalability, Machine Learning, Distributed Computing, Microsoft Azure, Information Privacy

  • Johns Hopkins University

    Skills you'll gain: Autoencoders, Recurrent Neural Networks (RNNs), Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Generative Model Architectures, Unsupervised Learning, Responsible AI, Data Ethics, Markov Model

  • Skills you'll gain: Autoencoders, Shiny (R Package), Deep Learning, Recurrent Neural Networks (RNNs), Transfer Learning, Convolutional Neural Networks, Fine-tuning, Image Analysis, Artificial Neural Networks, PyTorch (Machine Learning Library), Applied Machine Learning, Tensorflow, Predictive Modeling, Model Optimization, Model Training, Interactive Data Visualization, Time Series Analysis and Forecasting, Model Evaluation

  • Skills you'll gain: Model Deployment, Transfer Learning, Keras (Neural Network Library), Fine-tuning, Deep Learning, Applied Machine Learning, Tensorflow, Recurrent Neural Networks (RNNs), PyTorch (Machine Learning Library), Convolutional Neural Networks, Artificial Neural Networks, Machine Learning Methods, Model Optimization, Model Training

  • Skills you'll gain: Model Optimization, Dimensionality Reduction, Unsupervised Learning, Deep Learning, Machine Learning Algorithms, Applied Machine Learning, Random Forest Algorithm, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Anomaly Detection, Classification Algorithms, Linear Algebra