Apache Spark Training Apache System Big data Data Science Data Science with 'Python' Deep learning Keras Machine learning Practical Statistics Pytorch TensorFlow
The score is based on the quality of the course content & user experience as rated by the learners.
Learning Experience
8.9
Content Rating
8.5
PROS:
Great Introductory course for Big Data Analytics
Exercises and assignments have the appropriate level of difficulty
Interesting concepts with more math
Go deep in machine learning and signal processing with different datasets
Worthy course programs for the price offered
CONS:
The concepts ain't explained completely here (being advanced course)
Apache Spark Training Artificial intelligence Data Engineering Data Science Data Science with 'Python' Deep learning Keras Machine learning Pytorch TensorFlow
The score is based on the quality of the course content & user experience as rated by the learners.
Learning Experience
8.8
Content Rating
8.8
PROS:
Useful information on an introduction to Deep Learning and Neural Networks with Keras.
Demonstration of an understanding of supervised deep learning.
You can apply your AI and Neural Network skills to a real-world challenge also can demonstrate your ability to communicate project outcomes.
CONS:
Need to improve the content on Scalable Machine Learning and on Big Data using Apache Spark.
Application Programming Interfaces (API) Artificial intelligence Building AI Chatbots Data Science Deep learning IBM Watson Studio Natural language processing
The score is based on the quality of the course content & user experience as rated by the learners.
Learning Experience
9.3
Content Rating
9.5
PROS:
Excellent program for beginners
Get familiar and know more about Watson services
Informative content throughout, logically laid out and well presented
CONS:
Need more detailed view of IBM Cloud platform
Need more exercises on tools of IBM Watson
Course content needs to be updated to the latest changes
Linear Algebra Machine Learning Basics Probability Basics Python for Data Science Statistics Basics
Apache Spark Training Apache System Artificial intelligence Data Science Data Science with 'Python' Deep learning IBM Watson Studio Machine learning Natural language processing
This score is based on the user experience as rated by the learners
Learning Experience
8.6
PROS:
Very well structured course to understand whole AI workflow
Labs for Hands-on session are useful
Case studies are challenging and informative
CONS:
Content could be more in-depth as an 'advance' course
More practicality and assignment should be helpful
Artificial intelligence Building AI Chatbots Data Science with 'Python' Machine learning Natural language processing
The score is based on the quality of the course content & user experience as rated by the learners
Learning Experience
9.0
Content Rating
9.2
PROS:
The course module has been designed especially for beginners to understand the basics of AI.
The course on building AI-powered chatbots seems to be very informative, logically laid out, and well presented, as it is a great platform to learn AI-powered Chatbots without programming with Watson Assistant.
Excellent course for understanding the basics of python and introduction to Pandas and Numpy.
Useful information on an introduction to computer vision modeling, OpenCV, and its related projects.
CONS:
Users expect more exercise involving the tools of Watson.
Building an AI power chatbot course should be updated to reflect the latest changes in the Watson Conversation interface.
In the python for data science & AI course, the instructions for IBM Watson and how to set up the assignments are outdated.
Artificial intelligence Cloud Databases Data Analysis Data Science Data Science with 'Python' Data Visualization Machine learning Predictive Modelling SQL for Data Science
The score is based on the quality of the course content & user experience as rated by the learners.
Learning Experience
9.2
Content Rating
9.1
PROS:
The course module has been designed especially for beginners to understand the basics of Data Science.
Hands-on projects will help you to clear your technical concepts.
Course provides detail and clear information about Pandas, Numpy, statistical and data analysis.
CONS:
Users expect more exercise involving the tools of data science methodology.
Should have prior knowledge of calculus and linear algebra.
