Best Selling Instructor and Data Scientist Minerva Singh Provides 30 Hours of Content on Data Analysis, Visualization, Statistics, Deep Learning, and More
Minerva Singh is a Ph.D. graduate from Cambridge University where she specialized in Tropical Ecology. She is also a Data Scientist on the side. As a part of her research, she has to carry out extensive data analysis, including spatial data analysis using tools like R, QGIS, and Python. Minerva also holds an MPhil degree in Geography and Environment from Oxford University. She has more than 64 thousands learn her courses and a lot of students have placed the positive feedback about her courses.
Business Data Visualization, Analytics and Reporting with Google Data Studio
Master a Free Tool for Data Analytics and Business Intelligence
Google Data Studio (GDS) is a free dashboard and reporting tool (which lives in the cloud). It allows you to create dynamic, collaborative reports, and visualization dashboards. Paid Business Intelligence and Data Analytics Tools Like Tableau Are have either plateaued or will plateau soon. Many of these are either too expensive for small or teams or have a steep learning curve for beginners. This course helps you start with GDS and become proficient in producing powerful visualizations and reports.
Access 18 lectures and 2 hours of content 24/7
Gain familiarity with the interface of Google Data Studio
Lean to add your own data to GDS
Connect to different analytic tools such as Youtube Analytics and Google Ads
Implement different data tabulation techniques
Present the results as powerful and interactive reports
- Length of time users can access this course: lifetime
- Access options: desktop and mobile
- Certificate of completion included
- Redemption deadline: redeem your code within 30 days of purchase
- Updates included
- Experience level required: intermediate
Harness the Power of the H2O Framework For Machine Learning in R
Master Powerful R Package for Machine Learning, Artificial Neural Networks, and Deep Learning
In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By becoming proficient in machine learning, neural networks, and deep learning via a powerful framework, H2O in R, you can give your company a competitive edge and boost your career to the next level. This course covers the main aspects of the H2O package for data science in R. If you take this course, you can do away with taking other courses or buying books on R based data science as you will have the keys to a very powerful R supported data science framework.
Access 6 lectures and 1 hour of content 24/7
Be familiar with powerful R-based deep learning packages such as H2O
Learn the important concepts of machine learning without the jargon
Implement both supervised and unsupervised algorithms using H2O
Do Artificial Neural Networks (ANN) and Deep Neural Networks (DNN)
Work with real data within the framework
Statistics and Machine Learning For Regression Modelling With R
Learn Hands-On Regression Analysis for Practical Statistical Modeling and Machine Learning in R
Regression analysis is one of the central aspects of both statistical and machine learning-based analysis. This course will teach you regression analysis for both statistical data analysis and machine learning in R in a practical hands-on manner. This course can help you achieve better grades, give you new analysis tools for your academic career, implement your knowledge in a work setting, or make business forecasting related decisions.
Access 50 lectures and 6 hours of content 24/7
Implement and infer Ordinary Least Square (OLS) regression using R
Build machine learning-based regression models and test their robustness in R
Apply statistical and machine learning-based regression models to deals with problems such as multicollinearity
Learn when and how machine learning models should be applied
Master PyTorch For Artificial Neural Networks (ANN) and Deep Learning
Get Introduced to Deep Neural Networks and Become a Pro in Practical PyTorch-Based Data Science
This is a complete neural network and deep learning training with PyTorch in Python. It's a full 6-hour PyTorch Bootcamp that will help you learn basic machine learning, how to build neural networks, and explore deep learning using one of the most important Python Deep Learning frameworks. In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal and the advent of frameworks such as PyTorch is revolutionizing deep learning. By gaining proficiency in PyTorch, you can give your company a competitive edge and boost your career to the next level.
Access 52 lectures and 6 hours of content 24/7
Learn implement deep learning models with PyTorch
Implement PyTorch based deep learning algorithms on imagery data
Configure the Anaconda Environment for getting started with PyTorch
Implement common machine learning algorithms for Image Classification
Image Processing and Analysis Bootcamp with OpenCV and Deep Learning in Python
Implement Both Machine Learning and Deep Learning Techniques in a Hands-On Manner
This course is your complete guide to practical image processing and computer vision tasks using Python. It covers the important aspects of Keras and Tensorflow (Google's powerful Deep Learning framework) and if you take this course, you can do away with taking other courses or buying books on Python Tensorflow and Keras based data science. In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal and advent of Tensorflow and Keras is revolutionizing Deep Learning. By gaining proficiency in Keras and Tensorflow, you can give your company a competitive edge and boost your career to the next level.
Access 61 lectures and 5 hours of content 24/7
Get started with the Python data science environment
Read in image data into the Jupiter/iPython environment
Carry out basic image pre-processing and computer vision tasks with Python
Implement Unsupervised Learning Algorithms on image data
Keras Bootcamp For Deep Learning and AI in Python
Master Keras: An Important Deep Learning Framework for Deep Learning and Artificial Intelligence
This is a full 3-hour Python Keras Neural Network and Deep Learning Boot Camp that will help you learn basic machine learning, neural networks and deep learning using one of the most important Deep Learning frameworks—Keras. This course is your complete guide to the practical machine and deep learning using the Keras framework in Python. This means, this course covers the important aspects of Keras (Google's powerful Deep Learning framework) and if you take this course, you can do away with taking other courses or buying books on Python Keras based data science.
Get started with Jupyter notebooks for implementing data science techniques
Understand the basics of Keras syntax
Create artificial neural networks and deep learning structures with Keras
Complete Artificial Neural Networks and Deep Learning In R - Product Image
Complete Artificial Neural Networks and Deep Learning In R
Discuss Artificial Intelligence and Machine Learning for Practical Data Science in R
Dive into R data science using real data in this comprehensive, hands-on course. Get up to speed with data science packages like caret, h20, MXNET, as well as underlying concepts like which algorithms and methods are best suited for different kinds of data. Help your company scale by becoming an R expert!
Access 51 lectures and 5 hours of content 24/7
Get introduced to powerful R-based deep learning packages such as h2o and MXNET
Explore deep neural networks (DNN), convolution neural networks (CNN) and recurrent neural networks (RNN)
Learn to apply these frameworks to real life data for classification and regression applications
Data Analysis Masterclass With Statistics and Machine Learning In R
Learn How to Work With Time Series/Temporal Data Using Statistical Modelling and Machine Learning Techniques in R
This course is your complete guide to time series analysis using R. So, all the main aspects of analyzing temporal data will be covered n depth. You’ll start by absorbing the most valuable R Data Science basics and techniques. It uses easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R. This course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real-life.
Access 52 lectures and 5 hours of content 24/7
Get an introduction to powerful R-based packages for time series analysis
Learn commonly used techniques, visualization methods and machine/deep learning techniques that can be implemented for time series data
Apply these frameworks to real life data including temporal stocks and financial data