Apache Hadoop Training Apache Spark Training Data Mining Data Science Data Science with 'R' Data Visualization Data Wrangling Machine learning Practical Statistics
The score is based on the user experience, rated by the learners
Learning Experience
9.5
PROS:
Excellent content will clear your conceptually doubts.
Good collaboration of practical & theoretical knowledge.
Systematic, well organized and supportive faculties.
Probability Basics Up-to-date browser required for programming
Data Analysis Data Science Data Science with 'R' Data Visualization Data Wrangling Machine learning Practical Statistics Probability Regression Analysis
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.
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In the python for data science & AI course, the instructions for IBM Watson and how to set up the assignments are outdated.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.
Basic Scripting in Python Fundamentals of calculus Linear Algebra Probability Basics Statistics Basics
Artificial intelligence Data Analysis Data Science Data Science with 'Python' Deep learning Machine learning Regression Analysis Reinforcement learning SQL for Data Science
The score is based on the quality of the course content & user experience as rated by the learners
Learning Experience
9.3
Content Rating
9
PROS:
Well-structured course and easy-to-understand lectures
Lots of Labs to get a hands-on practice
Good examples to cover the major topics
CONS:
Required in detailed explanation on hypothesis testing
