The most common question that we often come across on discussion boards is –“Which data science training should I go for?” People often ask- “Is Coursera’s Data Science Specialization better than Udacity?” or “Should I take ProjectPro’s IBM Certified Data Science Training?” or the question could be about some other data science training academy. Whatever be the question, the innate reason behind such questions is the dilemma people go through when they are about to enrol for a data science course.
With increasing data science tools, analysis techniques and eLearning providers - the decision to enrol for a data science training from one of the MOOC’s providers is not an easy one. However, data science courses might vary by company names but their curriculum is designed to help students learn data cleaning, data munging, data analysis, dealing with big datasets to solve business problems, make predictions with certainty and effectively communicate the results using apt data visualization tools. So, irrespective of the fact that you choose Coursera Data Science Course or ProjectPro Data Science Training- the ultimate objective is to help students/professional acquire the required skills to become a Data Scientist. What follows is an overview of Coursera Data Science and ProjectPro Data Science course structure.
From predicting the path of contagious diseases to tracking customer behaviour - data science is being applied for creating big data solutions for solving complex real-world problems. As the demand for applications of data science continues to rise, there is a simultaneous increase in the demand for skilled data scientists. The Data Science discipline is opening up scores of opportunities with lucrative salaries for professionals having usable data science skills with an accredited Data Science Certification.
If you want to learn data science and become a data scientist, then please do your research on all the courses that are available for you online. Coursera Data Science and ProjectPro Data Science courses are 2 of the few online data science trainings which is open for all and provide an interactive platform to learn data science and get job-ready for the role of a data scientist.
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ProjectPro's data science course is devloped in joint partnership with IBM to ensure that it is in-line with data science industry trends. The instructors, data science projects and the quality of course are supervised by IBM. ProjectPro Data Science Training is categorized into series of two data science courses –
The main objective of ProjectPro’s data science training is to help professionals or students learn to create data science products and solutions by working on comprehensive hands-on projects approved by IBM. There is very little theory involved, except to explain the concepts. Students can enrol for any of the course first and then move on to take the next one - as having experience in both Python and R would help with the job role of a data scientist. ProjectPro’s data science in Python and R programming, focus on learning the data science concepts through coding under the guidance of industry experts from Day 1.
This course curriculum is designed to help students learn right from the basics of Python programming to various analysis and machine learning techniques - through four different projects –
1) Beer Recommendation System
Learn about basic concepts of Python and various data science libraries like Pandas, NumPy, Pylab, etc.
2) Restaurants recommendation
Learn about various machine learning concepts like collaborative filtering, Pearson coefficient, Bayesian Model, K-Nearest Neighbour Algorithm, etc.
3) Predicting Stock Market Returns
Learn about SVM, RandomForest, Logistic and Linear Regression models, plotting, etc.
4) Africa Soil Property Prediction
Learn about Exploratory data analysis, Ridge linear regression, lasso regression, etc.
ProjectPro’s data science in R programming course is focussed on helping students understand the various functions to extract, explore and clean data, learn the packages used for machine learning in R, learn about various visualization tools in R through 5 different hands-on projects –
1) Print sitting pattern in a plane
Learn about the basic concepts in R like objects, data types, attributes, loops, functions, vectorized operations, etc.
2) Data Cleaning from Different Sources
Students get to work on a project that reads the data of a company from various sources. This projects helps understand using dplyr, reading files, managing data frames, writing regular expressions, etc.
3) Analysis of white wine quality based on different parameters and customer feedback
Learn the basics of mathematics and statistics like conditional probability, P values, Bayes rule, Hypothesis testing, bootstrapping, etc.
4) Building different graphs and use of visualization techniques on given data
Having said that data visualization is a key skill for data scientist-this project familiarizes the students on how to plot graphs using ggplot2.
5) Predicting credit card defaulter
This projects helps in understanding about the various machine learning techniques and different regression models like Logistic regression, passion regression, multivariable regression, etc.
Students are accredited with an individual IBM certification on completion of either the Data Science in Python course or Data Science in R programming - if they opt for the IBM track. At the end of the course, few additional benefits that students get to avail are career guidance from the industry experts, tips on the various companies that are currently hiring data scientists, they get to know about the frequently asked interview questions and advice on data science resume writing guidelines.
Coursera Data Science specialization course, created by John Hopkins University is categorized into a series of 9 short courses that covers the basic concepts of data science and the tools (particularly focussed on the usage of R programming) that are required for data analysis. Coursera data science provides a Capstone project once you earn verified certificates in all the 9 short courses that test your mastery of the skills in the data science courses. Students/Professionals can also enrol for any of the short courses (individually) under Coursera Data Science specialization but they will not get a certificate for the same.
Pre-requisites to enrol for Coursera Data Science specialization include basic knowledge of linear algebra and fundamental programming experience. Course modules covered under Coursera Data Science Specialization that are offered monthly, include –
Coursera Data Science specialization will provide you a basic understanding of the data science discipline using R language by addressing the high level aspects of data science. The first 4 short series of courses offered, will help you learn R for data analysis. However, people who do not hail from a programming background might face some difficulties if they are held up with some coding tasks that are not explained in the course material. The rescue to this, is to search through the discussion forums and ask questions to find the solutions to the programming problems they have been stuck with. Coursera Data Science specialization by John Hopkins University not only focuses on helping students learn how to practice Data Science using R programming language, but helps get a good understanding of machine learning and statistical techniques.
Before you compare any of the data science programs and decide to enrol, do consider these factors:
Still confused on how to decide? Read what one of the students had to say who has taken both Coursera Data Science Specialization and ProjectPro Data Science training – Click Here
We hope to have provided the best possible information about Coursera Data Science Course and ProjectPro Data Science Training. If you plan to enrol for a data science training soon, do go through the above listed factors and choose a course that provides the highest value for you and best fits your learning requirements. You should by now have found your path through one of the data science trainings and are all set to make the right decision.
If you have already attended either one of these Data Science Trainings, please share your reviews in the comments below.