Building Chatbots in Python
Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.
Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.
Learn techniques to extract useful information from text and process them into a format suitable for machine learning.
Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.
Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.
Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.
Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.
In this course you will learn the details of linear classifiers like logistic regression and SVM.
In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.
Learn to process, transform, and manipulate images at your will.
Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.
Gain experience using techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.
Learn about ARIMA models in Python and become an expert in time series analysis.
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.
Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.
Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.
Start your reinforcement learning journey! Learn how agents can learn to solve environments through interactions.
In this course you'll learn to use and present logistic regression models for making predictions.
Learn how to detect fraud using Python.
Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.
Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.
Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.
Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.
Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.
This course will introduce the support vector machine (SVM) using an intuitive, visual approach.
Learn how to approach and win competitions on Kaggle.
Learn the bag of words technique for text mining with R.
Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.
Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.
Learn how to tune your model's hyperparameters to get the best predictive results.
Learn to detect fraud with analytics in R.
Learn to process sensitive information with privacy-preserving techniques.
Learn how to prepare and organize your data for predictive analytics.
Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.
Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.
Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.
In this course, you'll learn how to implement more advanced Bayesian models using RJAGS.
Navigate and use the extensive repository of models and datasets available on the Hugging Face Hub.
Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.
Master the essential skills of data manipulation in Julia. Learn how to inspect, transform, group, and visualize DataFrames using real-world datasets.
This course is for R users who want to get up to speed with Python!
Data storytelling is a high-demand skill that elevates analytics. Learn narrative building and visualizations in this course with a college major dataset!
Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.
Take your reporting skills to the next level with Tableau’s built-in statistical functions.
Learn about string manipulation and become a master at using regular expressions.
Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!
Discover how to begin responsibly leveraging generative AI. Learn how generative AI models are developed and how they will impact society moving forward.
Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.
Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.
Learn the nuts and bolts of LLMs and the revolutionary transformer architecture they are based on!