The data science role is one of the most in-demand skills in an era where data and software rule. A data scientist is responsible for making sense of the massive data that a business generates from its operations and extracting actionable insights that are valuable for objective decision-making in the organization. This helps organizations solve problems and formulate growth strategies.
The journey to becoming a seasoned data scientist is a taxing but worthwhile one. In addition to undertaking a PG in Data Science or other well-recognized certification training, you need to not only develop practical skills in statistics, programming, data visualization, machine learning, and domain knowledge but also have a portfolio to demonstrate that you possess these skills.
Part of the learning journey is deciding which specific data science certification training you will pursue. This article compares two data science courses, the post-graduate data science and engineering program offered by Great Learning and the Master’s data science program by Edureka.
Post Graduate Data Science and Engineering Program, Great Learning
Great learning was founded in 2013 with the vision of equipping current professionals with future-proof skills in the dynamic IT field. The Post Graduate Data Science and Engineering Program is one of the certification courses offered at Great Learning. It is designed for both professionals who are already in the field and fresh graduates trying to find their footing in the field, typically professionals with less than three years of experience.
This program is divided into four main modules divided into three to four topics per module. It is packed with five projects and at least one project for every topic making it a very practical course. Towards the end of the course is a capstone project that will test most of the concepts the learners have learned through the course with real-world data sets as well as career preparation and skills development training, which serve as the greatest highlights for this course.
Great Learning offers learners two learning options to give learners the flexibility of studying online or in-classroom. The five-month in-person classroom learning takes place from Monday to Thursday from 9.30 am.
The live online learning sessions are offered four hours per week after working hours between Monday and Friday, as well as four hours every weekend dedicated to practical online lab sessions and projects. It takes nine months to complete the course through the online learning option.
Both courses include four weeks of undertaking the capstone project towards the end of the course.
This course covers four broad modules, including the
- Data science foundation
- Machine learning techniques
- Data engineering
- Domain application
Python programming language, Tableau for visual analytics, and MySQL relational database management system
The general prerequisites for undertaking a data science course are mathematics, programming, data processing, statistical analysis, and data visualization skills. However, for this program, one needs to be either in their final semester or recent graduates with less than three years of experience.
At the end of the program, learners are awarded a Great Learning certification.
The Post Graduate Data Science and Engineering course is a comprehensive program designed by data science experts. A notable highlight is the fact that Great Learning has partnered with over 150 corporate companies to drive its placement program and accord learners the opportunity for networking, mentorship, and professional project evaluation. The placement program includes benefits such as aptitude and skills training and development as well as interview preparation.
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Data Science Masters Program, Edureka
Edureka was founded in 2011 as an e-learning platform to give students the alternative learning option to complete courses by attending live online courses facilitated by a team of committed educators. The Data Science Master’s program offered by Edureka is designed to cater to anyone who is interested in pursuing data science as a career, whether an experienced professional in the IT industry or a beginner just venturing into the data science field.
As it caters to both beginners and experienced professionals, the data science master’s program is comprehensive and covers data management, statistics, machine learning, and big data alongside the tools used by data scientists like Tableau for data visualization, Python, Apache Spark, and TensorFlow. By the end of this program, learners will have mastered data extraction and exploration techniques as well as machine learning algorithms.
The data science master’s program comprises seven compulsory courses and five free elective courses with a capstone project at the end of the program. The courses are:
- Python statistics for data science
- R statistics for data science
- Data science certification course using R
- Data science certification training using Python
- Apache Spark and Scala certification training
- Deep learning training – TensorFlow certification
- Tableau certification training
- SQL essentials training and certification
- R programming certification training
- Python programming certification training
- Scala essentials
- MongoDB training and certification
Each individual course is either self-paced or online instructor-led and is designed to take a specific number of hours to equip learners with a number of skills. For instance, the R statistics for data science course takes 18 hours to complete and will equip learners with a total of 14 skills. Learners have the flexibility of taking courses in any order that they prefer. Learners will be awarded certification for each individual course they will complete.
Instructor-led courses are the Data Science Certification Course using R, Python Certification Training for Data Science, Apache Spark and Scala Certification Training, AI & Deep Learning with TensorFlow, Tableau Training & Certification. The others, including Python Statistics for Data Science Course, R Statistics for Data Science Course, SQL Essentials Training & Certification, R Programming Certification Training, Python Programming Certification Training, Scala Essentials, and MongoDB Training and Certification, are self-paced.
To earn the Master’s program certification, a learner should have completed the compulsory courses together with the capstone project. The elective courses are only meant to equip learners with additional data science skills and are not mandatory to earn the Master’s certification.
There are no prerequisites to enroll in this program. However, some basic skills one needs to have to pursue a data science course include programming, mathematics, statistical analysis, and data visualization skills.
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The advantage that the data science masters program by Edureka has over the others is that first, it caters to all individuals, experienced professionals, and beginners alike without placing a cap on the years of experience. The elective courses are most beneficial for beginners who may want to lay a foundation for the data science basic skills. Secondly, this program is very flexible. In addition to offering both self-paced and online instructor-led courses, students can take courses in the order that they prefer, and certificates will be awarded for individual courses.
Both courses are valuable to individuals as they offer unique but worthwhile benefits. If you are interested in mentorship and placement during and after completing the program, the post-graduate data science program by Great Learning will suit you. If you prefer the flexibility that comes with planning your learning path, the data science master’s program by Edureka will come in handy.