Micro-credentials
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- Udacity
- Microdegree
- Self-paced
- Beginner
- 1-3 Months
- Paid Course (Paid certificate)
- English
- Python
- Jupyter Notebook
- Basic Computer Literacy Linear Algebra Previous Programming Experience
- Artificial intelligence Calculus Essentials Data Science with 'Python' Deep learning Linear Algebra Essentials Neural Networks Pytorch
The score is based on the user experience, rated by the learners.
PROS:
- Excellent course for learning the fundamentals of AI.
- As compared to other training programs it is clear and meaningful.
- Concise and beginner friendly course material provided.
- Math concepts explanations are awesome.
CONS:
- Lesson on matplotib and seaborn needs more explanation.
- Very lengthy elementary content.
Best seller 
- Udacity
- Kaggle Mode
- Microdegree
- Self-paced
- Intermediate
- 3+ Months
- Paid Course (Paid certificate)
- English
- Python
- Basic Scripting in Python Basic SQL
- Data Analysis Data Science with 'Python' Data Visualization Data Wrangling Practical Statistics
The score is based on the user experience, rated by the learners.
PROS:
- Informative content as well as format of the video materials.
- Provides high quality lectures with many real industry cases plus tons of hands-on projects.
- The lectures and short exercises are well arranged.
CONS:
- One must have glimpses of Python standard libraries.
- Need some working experience with Pandas and NumPy.
- Need to reduce complexity of the course.
- Udacity
- Amazon Web Services Kaggle
- Microdegree
- Self-paced
- Advanced
- 1-3 Months
- Paid Course (Paid certificate)
- English
- Python
- Intermediate Machine Learning Proficiency in Python
- Data Engineering Data Science with 'Python' Deep learning Machine learning Natural language processing Software Engineering for Data Science
The score is based on the user experience, rated by the learners
PROS:
- Well organized instructions with concrete and familiar examples.
- Projects and reviewers will give you precious feedback.
- Unique, well-paced and well-structured content.
CONS:
- Should have deeper dive into machine learning algorithms.
- You need to be familiar with programming libraries like Numpy & pandas.
- Coursera
- University of California, San Diego
- Microdegree
- Self-paced
- Beginner
- 3+ Months
- Free Trial (Paid Course & Certificate)
- English
- Apache Hadoop Apache Spark
- None Pre-requisite
- Apache Hadoop Training Apache Spark Training Big data Data Modeling Machine learning
PROS:
- Well structured course with a solid foundation and real-world problems
- Provides a good overview and positioning of relevant big data technologies.
- Step by step approach from basics of big data to Hadoop framework with hands-on mapping
- Nice course to describe the traditional data modeling (RDBMS)
CONS:
- Some exercises are a bit difficult to understand
- The section on Spark needed more time and additional descriptions
- Udacity
- Insight
- Microdegree
- Self-paced
- Intermediate
- 3+ Months
- Paid Course (Paid certificate)
- English
- Python
- Intermediate SQL Linear Algebra Proficiency in Python
- Apache Cassandra Training Apache Spark Training AWS Cloud Databases Data Engineering Data Science
The score is based on the user experience, rated by the learners.
PROS:
- Clarity on explanation, all the tasks and demos.
- Projects are challenging and useful.
- The course content explains both the theory and practicalities of each technology in an easy-to-understand manner.
- The lessons are well-organized and highly informative.
- Real world projects and feedback is extremely helpful.
CONS:
- Expectation to have a bit improvement in instructor’s presentation skill.
- Need to be familiar with basic programming libraries.
Best seller
$1,400.00
- EDX
- University of California, San Diego
- Microdegree
- Self-paced
- Advanced
- 3+ Months
- Paid Course (Paid certificate)
- English
- Apache Spark Jupyter Notebook
- Intermediate Calculus Linear Algebra Previous Programming Experience
- Apache Spark Training Big data Data Science Data Science with 'Python' Machine learning Practical Statistics Probability
PROS:
- You will learn the basics of Python for data science and how to use arrays, series and data frames.
- Build your confidence and basic knowledge to pursue more complex projects.
CONS:
- Interaction with instructors can be slow and limited.
- Jupyter section is UNIX heavy and can be troubling to perform on Windows machines.
- Codecademy
- Microdegree
- Self-paced
- Beginner
- 3+ Months
- Paid Course (Paid certificate)
- English
- Python
- None Pre-requisite
- Data Analysis Data Manipulation Data Science Data Science with 'Python' Data Visualization Data Wrangling Deep learning Natural language processing SQL for Data Science
- Coursera
- deeplearning.ai
- Microdegree
- Self-paced
- Intermediate
- 3+ Months
- Free Trial (Paid Course & Certificate)
- English
- Python
- Intermediate Python Skills Linear Algebra Machine Learning Basics
- Data Science Data Science with 'Python' Deep learning Machine learning Neural Networks TensorFlow
The score is based on the quality of the course content & user experience as rated by the learners
PROS:
- Effective conceptualization on Neural Network and Deep Learning.
- The Hyper parameter explanations are excellent.
- Great coding exercises, improve understanding of the importance of vectorization
- Deeper insight into how to enhance your algorithm and neural network and improve its accuracy.
- Content delivery from a very experienced deep learning practitioner
- Overview of existing architectures and certain applications of CNN's
CONS:
- Need's organized structure of assignment & exercises
- Automatic graders for programming assignments can be tricky
- Assignment in the 5th course more challenging than other segments of the specialization
$49.00
- Coursera
- University of Michigan
- Microdegree
- Self-paced
- Beginner
- 3+ Months
- Free Trial (Paid Course & Certificate)
- English
- Python
- None Pre-requisite
- Data Science with 'Python' Python Programming
PROS:
- Very comprehensive and easy to understand
- Beneficial course on object-oriented programming in python 3
- Functional project at the end helps to understand how recommendation systems work
- Hands-on practice with the Runestone Notebook Environment
CONS:
- Little bit challenging, requires completing of Course 1
- Runestone project needs debugging
$1,500.00
- EDX
- Massachusetts Institute of Technology
- Microdegree
- Instructor-led
- Advanced
- 1+ Years
- Paid Course (Paid certificate)
- English
- Python
- Comfort with Mathematical Reasoning Intermediate Calculus Intermediate Probability Intermediate Vectors and Matrices Proficiency in Python
- Big data Data Analysis Data Science Deep learning Machine learning Practical Statistics Probability
$49.00
- Coursera
- University of Michigan
- Microdegree
- Self-paced
- Beginner
- 1-3 Months
- Free Trial (Paid Course & Certificate)
- English
- Python
- High School-level Algebra
- Data Analysis Data Science with 'Python' Data Visualization Practical Statistics
PROS:
- Excellent course content, thoughtfully composed and carefully edited
- Helpful course for a newcomer in data science studies
- Supplementary material in Jupyter notebooks is extremely valuable
- A great introduction to regression and bayesian analysis in python
CONS:
- Python coding instruction itself could have been more detailed
- Codes can be refactored in a way that can be more suitable for reproducible studies