- Course platform: Edureka
- Level: For all
- Price: Paid course (with Certificate)
- Class length: 11 courses 200+ hrs
- Project: Capstone project
★★★★★
More details + Enroll
MASTERS20
The score is based on the user experience as rated by the learners.
PROS:
- Well structured curriculum
- Includes top five skills in business intelligence
- Customer centered applied project
CONS:
- Not enough reviews
- Course platform: Edureka
- Level: All
- Price: Paid course (with Certificate)
- Class length: 9 courses 200+ hrs
- Project: Capstone project
★★★★★
More details + Enroll
MASTERS20
The score is based on the user experience as rated by the learners.
PROS:
- This course will give you an edge over other competing candidates for job
- Course covers almost all corners of the data science and machine learning
CONS:
- Not enough reviews
- Course platform: Edureka
- Level: All
- Price: Paid course (with Certificate)
- Class length: 9 courses 200+ hrs
- Project: Capstone project
★★★★★
More details + Enroll
MASTERS20
The score is based on the user experience as rated by the learners.
PROS:
- Well designed curriculum
- Covers important aspects to master Big Data
CONS:
- Not enough reviews
- Course platform: Edureka
- Level: All
- Price: Paid course (with Certificate)
- Class length: 10 courses 200+ hrs
- Project: Capstone project
★★★★★
More details + Enroll
MASTERS20
The score is based on the user experience as rated by the learners.
PROS:
- Hands on experience with industry experts
- You can gain end-to-end skills in DevOps
- Quora review: Course has everything to make you DevOps professional
- Quora review: Very comprehensive, syllabus conforming standards required by IT industry
CONS:
- Quora review: Expensive program
- Course platform: Edureka
- Level: All
- Price: Paid course (with Certificate)
- Class length: 12 courses 200+ hrs
- Project: Capstone project
★★★★★
More details + Enroll
MASTERS20
The score is based on the user experience as rated by the learners.
PROS:
- User with minimal IT experience found this course valuable
- Course begins with basics in Python and fundamentals of cloud computing
- Program curriculum is well designed
CONS:
- No user feed back / reviews for this program
- Course platform: Edureka
- Level: For all
- Price: Paid course (with Certificate)
- Class length: 10 courses 250+ hrs
- Project: Capstone project
★★★★★
More details + Enroll
MASTERS20
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.
- Course platform: Edureka
- Level: For all
- Price: Paid course (with Certificate)
- Class length: 12 courses 250+ hrs
- Project: Capstone project
★★★★★
More details + Enroll
MASTERS20
The score is based on the user experience, rated by the learners
PROS:
- Data science master programs sub courses will let you gain expertise in data science domain.
- Immediate assistance from experts throughout the learning journey.
- No any prior requirements for enrollment of this course.
CONS:
- Lengthy elementary content of Python Statistics for Data Science Course.
- Master Program is designed and developed only to accommodate various professional backgrounds.
- Course platform: Edureka
- Level: Advanced
- Price: Paid course (with Certificate)
- Class length: Approx. hrs.
★★★★★
More details +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.
- Course platform: Edureka
- Lifetime Access
- Level: Intermediate
- Price: Paid course (with Certificate)
- Class length: Approx. hrs.
★★★★★
More details +The score is based on the user experience, rated by the learners
PROS:
- Well presented module with good pace.
- Overall course material, description and homework will let you gain expertise in this domain.
- Constant updation on courses with 24X7 support with instant response from faculties.
CONS:
- Need to update more information on topics such as Statistical Inference.
- Course platform: Edureka
- Lifetime Access
- Level: All Levels
- Price: Paid course (paid Certificate)
- Class length: Approx. 44 hrs
★★★★★
More details +The score is based on the user experience, rated by the learners
PROS:
- Batches are available in very convenient time slots.
- Excellent presentation of detailed data wrangling.
- Explanations are easy, clean and very easy to understand.
CONS:
- You should be familiar with programming fundamentals and Statistics Essentials
- One should have familiarity with basic concepts about Python programming.
- Course platform: Edureka
- Lifetime Access
- Level: All Level
- Price: Paid course (with Certificate)
- Class length: Approx. 30 hrs
★★★★★
More details +The score is based on the user experience, rated by the learners
PROS:
- Excellent content will clear your conceptually doubts.
- Good collaboration of practical & theoretical knowledge.
- Systematic, well organized and supportive faculties.
CONS:
- Lengthy elementary content.
- Need brief information about R programming.
- Course platform: Edureka
- Lifetime Access
- Level: All Level
- Price: Paid course(with Certificate)
- Class length: Approx.30 hrs.
★★★★★
More details +The score is based on the user experience, rated by the learners
PROS:
- Well-structured programs and project submissions.
- Good overview and insight on the real world application.
- Interactive training method and interesting content.
CONS:
- This course needs to have in-depth exercises.
- Need more description for the topics- Linear regression & data mining
