Social And Emotional Learning Courses

Coursera

Sentiment Analysis with Deep Learning using BERT

Learn to build a powerful sentiment analysis model using BERT, covering data analysis, model architecture, optimization, and performance monitoring for multi-class classification.

• Coursera
• 2 hours 15 minutes
• Self-Paced
• Paid Course

Coursera

Build a Machine Learning Web App with Streamlit and Python

Create an interactive ML web app using Streamlit and Python, allowing users to choose algorithms and set parameters without coding, in under 100 lines of code.

• Coursera
• 2 hours
• Self-Paced
• Paid Course

AI Workflow: Machine Learning, Visual Recognition and NLP

Explore machine learning, visual recognition, and NLP in AI workflows. Learn evaluation metrics, model selection, and best practices for linear models, tree-based algorithms, and neural networks using IBM Watson.

• Coursera
• 13 hours 41 minutes
• Self-Paced
• Paid Course

Alberta Machine Intelligence Institute

Optimizing Machine Learning Performance

Synthesize applied ML knowledge to create a maintenance roadmap, analyze changing data, identify unintended effects, and operationalize models for confident project rollout and optimization.

• Coursera
• 11 hours 37 minutes
• Self-Paced
• Paid Course

Introduction to Deep Learning & Neural Networks with Keras

. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what is deep learning, and how do deep learning models compare to artificial neural networks?

• Coursera
• 10 hours 10 minutes
• Self-Paced
• Paid Course

AI Capstone Project with Deep Learning

Apply deep learning to real-world challenges: load data, build and validate models, and present results. Gain hands-on experience with image classification using pre-trained networks like ResNet and VGG16.

• Coursera
• 14 hours 34 minutes
• Self-Paced
• Paid Course

Deep Learning with Keras and Tensorflow

Discover hidden structures in unstructured data using TensorFlow. Learn to build and apply deep learning models for various data types to solve real-world problems.

• Coursera
• 23 hours 21 minutes
• Self-Paced
• Paid Course

Google Cloud;  New York Institute of Finance

Introduction to Trading, Machine Learning & GCP

Explore trading fundamentals, machine learning, and Google Cloud Platform to build quantitative strategies and models using Python, focusing on regression, time series, and neural networks.

• Coursera
• 5 hours 25 minutes
• Self-Paced
• Paid Course

New York Institute of Finance;  Google Cloud

Using Machine Learning in Trading and Finance

Explore machine learning techniques for advanced trading strategies, including quantitative, pairs, and momentum trading. Learn to design, build, and back test models using TensorFlow and Keras.

• Coursera
• 7 hours 58 minutes
• Self-Paced
• Paid Course

New York Institute of Finance;  Google Cloud

Reinforcement Learning for Trading Strategies

Explore reinforcement learning for trading strategies, covering neural networks, LSTMs, and AutoML. Learn to build RL-based trading systems and optimize portfolios using advanced machine learning techniques.

• Coursera
• 12 hours 16 minutes
• Self-Paced
• Paid Course

Smart Analytics, Machine Learning, and AI on Google Cloud

Explore machine learning integration in Google Cloud data pipelines, from AutoML to custom solutions with Notebooks, BigQuery ML, and Vertex AI for enhanced data insights.

• Coursera
• 6 hours 36 minutes
• Self-Paced
• Paid Course

Alberta Machine Intelligence Institute

Data for Machine Learning

Develop skills to prepare, engineer, and validate data for machine learning models. Learn to identify biases, improve generality, and enhance model accuracy through thoughtful feature engineering.

• Coursera
• 11 hours 53 minutes
• Self-Paced
• Paid Course

Alberta Machine Intelligence Institute

Introduction to Applied Machine Learning

Comprehensive introduction to machine learning for professionals, covering problem definition, data preparation, and real-world applications across various domains. Develop skills to identify ML opportunities and translate business needs into ML solution…

• Coursera
• 6 hours 46 minutes
• Self-Paced
• Paid Course

Alberta Machine Intelligence Institute

Machine Learning Algorithms: Supervised Learning Tip to Tail

Explore supervised learning techniques like decision trees, k-NN, and SVMs. Implement and analyze these algorithms on real business cases, gaining practical skills in data preparation and model evaluation.

• Coursera
• 9 hours 24 minutes
• Self-Paced
• Paid Course

Scalable Machine Learning on Big Data using Apache Spark

Learn to scale machine learning tasks on big data using Apache Spark. Gain hands-on experience with parallel processing, distributed storage, and SparkML Pipelines to handle petabyte-scale datasets efficiently.

• Coursera
• 6 hours 38 minutes
• Self-Paced
• Paid Course