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$29.99
- Udemy
- Lazy Programmer Team Inc.
- Online Course
- Self-paced
- Advanced
- 1-4 Weeks
- Paid Course (Paid certificate)
- English
- Artificial intelligence Data Science with 'Python' Deep learning TensorFlow
The score is based on the learner ratings/experience, at Udemy.
PROS:
- Covers a wide-range of advanced reinforcement learning topics.
- Excellent and advanced topics.
- Good details and manual coding.
- Concise details about each algorithms.
CONS:
- Should have more explanation on the theory.
- Need to improve coding lectures.
$149.00
- EDX
- Harvard University
- Online Course
- Self-paced
- Advanced
- 1-4 Weeks
- Free Course (Affordable Certificate)
- English
- Bioinformatics Data Analysis Genomics Research methodology
The score is based on the user experience as derived from class-central.com
PROS:
- The course makes up two self-paced Professional Certificates.
- Detailed information on advanced statistical concepts such as hierarchical models.
- Given the diversity in educational background of students they have divided the series into seven parts.
- Minimal time investment that yields a decent introduction to RNA-seq analysis.
CONS:
- Need more elaboration on some course topics.
- Massive datasets generated by these studies.
- Should increase the number of a programming exercise.
$49.00
- Coursera
- IBM
- Microdegree
- Self-paced
- Advanced
- 3+ Months
- Paid Course (Paid certificate)
- English
- Apache System Big data Data Science Data Science with 'Python' Deep learning Keras Machine learning Pytorch Spark TensorFlow
The score is based on the quality of the course content & user experience as rated by the learners.
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)
- The videos need to be updated
$49.00
- Coursera
- NRU Higher School of Economics
- Microdegree
- Self-paced
- Advanced
- 3+ Months
- Paid Course (Paid certificate)
- English
- Data Science Deep learning Machine learning Natural language processing TensorFlow
The score is based on the quality of the course content & user experience as rated by the learners.
PROS:
- In terms of quality of the material this course will absolutely meet your requirements.
- One with graduate level math skills can also commence with this course.
- Assignments are good for getting to know python tools.
CONS:
- Need to improve the quality of content in Bayesian methods for machine learning course.
- Require quite a bit of probability theory knowledge.
- The teachers should put more time into explaining the models and their details.
$199.00
- Edureka
- Online Course
- Self-paced
- Advanced
- Paid Course (Paid certificate)
- English
- Data Analysis Data Science Data Science with 'R'
The score is based on the user experience, rated by the learners
PROS:
- Overall well-presented modules, materials and homework helps you gain expertise in this domain.
- Comprehensive content and highly knowledgeable instructors.
- Real-life case studies on a project to implement techniques you learn.
- Each module contains practical assignments.
CONS:
- One should be familiar with Basic Understanding of R.
- Length elementary content.
- Simplilearn
- IBM
- Masters program
- Instructor-led
- Advanced
- Paid Course (Paid certificate)
- English
- Artificial intelligence Data Science Data Science with 'Python' Deep learning Keras Machine learning Natural language processing TensorFlow
The score is based on the user experience rated by the learners.
PROS:
- Online self-learning videos & trainers assistance with their enriched knowledge helps you understand the content easily.
- All the courses are well structured with self-learning, live classes, and assessment.
- Excellent industry-related projects and will help you to put into practice what you learned in the class.
CONS:
- Should have basic knowledge of mathematics.
- Need to be familiar with the fundamentals of Python programming.
- Udacity
- Bertelsmann Figure eight an appen co. IBM Insight Kaggle Starbucks
- Microdegree
- Self-paced
- Advanced
- 3+ Months
- Paid Course (Paid certificate)
- English
- Data Engineering Data Science Machine learning Natural language processing Spark
The score is based on the user experience, rated by the learners.
PROS:
- Program is comprehensive with all the required data.
- Transparent explanations and the exercises helps a lot to understand the content.
- Commencement with fundamental algorithm(math) before you implement it.
CONS:
- Need to add more related lessons for each algorithm.
- You should be familiar with SQL programming and statistics.
- Hands-on with wrangling and visualizing data.
- Udacity
- Amazon Web Services Kaggle
- Microdegree
- Self-paced
- Advanced
- 1-3 Months
- Paid Course (Paid certificate)
- English
- Data Engineering Data Science with 'Python' Deep learning Machine learning Natural language processing
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.
$149.00
- EDX
- Harvard University
- Online Course
- Self-paced
- Advanced
- 1-3 Months
- Free Course (Affordable Certificate)
- English
- Bioinformatics Data Analysis Genomics Research methodology
The score is based on the quality of the course content & user experience as derived from coursetalk.com
PROS:
- Project is a great idea for all people who had a real interest for less that is the course or the time of study in a great university.
- Throughout the case studies, you make use of exploratory plots to get a general overview.
- Given the diversity in educational background of students you will find the series divided into seven parts.
- Statisticians can consider skipping the first two or three courses.
CONS:
- Need prior knowledge of PH525.3x, PH525.4x.
- Could simplify the courses.
- Need more elaboration on some course topics.
- Simplilearn
- IBM
- Masters program
- Instructor-led Self-paced
- Advanced
- Paid Course (Paid certificate)
- English
- Data Analysis Data Science with 'Python' Data Science with 'R' Power BI Tableau
The score is based on the user experience rated by the learners.
PROS:
- Beginners are welcome to this course.
- The courses are very well designed and the live classes have personal attention in terms resolving the doubts.
- Very informative and concise information provided on Statistics.
CONS:
- Requires a foundation in statistics and mathematics.
$1,099.00
- Edureka
- Masters program
- Instructor-led Self-paced
- Advanced
- Paid Course (Paid certificate)
- English
- Data Analysis Data Science with 'R' SAS Tableau
The score is based on the user experience, rated by the learners
PROS:
- Upon enrolling in the course, one can start with his convenience.
- Personal learning managers will assist you to clear your queries.
- You can always switch to another batch, depending upon your availability.
CONS:
- Masters Program is designed and developed only to accommodate various professional backgrounds.
- Need to improve the content on Essentials for Analytics.
$49.00
- Coursera
- NRU Higher School of Economics
- Online Course
- Self-paced
- Advanced
- 1-4 Weeks
- Paid Course (Paid certificate)
- English
- Data Analysis Data Science
The score is based on the quality of the course content & user experience as rated by the learners.
PROS:
- Good and easy explanations on validation and metrics.
- Excellent framework for additional applications of projects.
- Chock full of practical information that is presented clearly and concisely.
- Packed with full of tips and tricks and techniques that are well explained and very useful for data science.
CONS:
- There are some pretty advanced tricks.
- Need to improve content on introductory-level material.
- Bit complex for those who do not have a good knowledge base on the subject of Machine learning.