Free Data Science Courses & Certifications

The Data Science for Smart Cities training is a 16-week course and requires the effort of six to nine hours every week. Purdue University has designed a programme that falls under the engineering category. Prof Satish Ukkusuri and Eunhan Ka will teach the intermediate level course. Language of the training and video transcripts are in English.

The focus of the Data Science for Smart Cities online programme is how to utilise scientific tools and techniques to analyse, infer, and predict large-scale data. Data present in city networks and collected from various sources such as social media, GPS vehicular data, mobile phones, social network, etc. will be used. The  Data Science for Smart Cities syllabus will introduce basic data science methods for the analysis of these datasets. The  Data Science for Smart Cities training will deal with these methods as well as applying those using Python for smart city issues. 

Candidates can enrol for the Data Science for Smart Cities certification without paying any fee. However, the ones interested in acquiring a verified certificate can do so by purchasing it. Additionally, the  Data Science for Smart Cities certificate will be signed by the instructor and have the university logo printed, making it a valuable addition to resumes or CVs.

Traditionally, research has been viewed as a purely academic undertaking, especially in resource-limited healthcare systems. Not all countries can afford clinical trials. As such, the findings and results of studies conducted in the United States and other Western and developed countries are generalised. The Collaborative Data Science for Healthcare course shines a light on why there is a need for localised research. 

The Collaborative Data Science for Healthcare programme aims to position research and data at the centre of all healthcare operations. It is an introduction and a survey of all the data science tools that are used in healthcare. The Collaborative Data Science for Healthcare syllabus includes numerous exercises and hands-on workshops to highlight the significance of a multi-disciplinary approach to data science in healthcare. 

Ideally, clinicians and engineers/computer scientists should take the Collaborative Data Science for Healthcare course together, as a team. This Collaborative Data Science for Healthcare classes on data analysis is brought to you by members of the MIT Critical Data team and is a 12-week long free online course. This self-paced programme can be taken either in the paid mode or in the free audit mode. The paid mode will provide unlimited access to the course as well as a certificate of completion whereas the free audit mode will give access only for a limited duration. 

The Data Wrangling with MongoDB online course is a part of the Data Analyst Nanodegree, offered by MongoDB, in association with Udacity. It will teach you about data wrangling from diverse sources and how to shape it to facilitate data-centred applications. You will also learn how to extract and gather data from popular data formats.

The Data Wrangling with MongoDB certification syllabus includes the fundamentals of data extraction, assessing data quality, and data cleaning’s best practices.  The curriculum has seven broad lessons that are further divided into different modules. You can finish the whole course in approximately 2 months. What’s more, instructors will familiarise you with MongoDB, data storing essentials, MongoDB’s query language, and its aggregation framework.

The Data Wrangling with MongoDB training by Udacity is a self-paced intermediate course that consists of multiple learning aids. These include instructional videos, practice exercises and quizzes. This is an excellent course if you want to apply for entry-level data science positions or are a working professional.

Data Science: Linear Regression online course offered by edX is an opportunity for the candidates to get insights about data science and linear regression. It covers implementation of linear regression and adjusting for confounding in practical work while using R. 

The Data Science: Linear Regression certification programme at a stretch of 8 weeks, gives its candidates exhaustive knowledge about linear regression and its applicability. The video-based, self-paced learning course is offered by Harvard University. The course is an ideal opportunity for the candidates to learn the subject through data-driven case studies for a better understanding of the subject. 

The Data Science: Linear Regression classes programme is free to access for everyone. However, to get the verified certificate, the candidate must need to upgrade to the verified track. During the audit track, the candidates will be able to access the course for free but that too only for a limited period. The Data Science: Linear Regression training is instructed by Rafael Irizarry, the professor of Biostatistics, at Harvard University, to make the candidates professionally skilled and enabled for a promising future ahead.

The Data Science: Productivity Tools certification course will be helping the students to organise and keep their projects and assignments in a structured way and reproduce the files and reports using tools namely- git, GitHub, RStudio and Unix/Linux. The Data Science: Productivity Tools online programme will be teaching the participants the different techniques to use the Linux and Unix tools for managing the data files and the directories that are present in the computer. Candidates will further be introduced and taught the importance of system git which is a powerful tool that will help to keep track in case there is some change in the tracks of the reports and files. 

The Data Science: Productivity Tools by edX will further help the applicants learn the basic functions while making a report in R functions and the ways to incorporate the provided code into the document. The eight-week Data Science: Productivity Tools certification programme will involve multiple projects and parts comprising- different scripts and data files. The course offers 2 tracks of study that can be chosen by the candidates - one is the audit and the other is the verified track. In these 2 tracks, the candidates can study in a self-paced mode. Though the course can be learnt by self, the candidates will have limited access to materials during the audit mode, and unlimited access during the verified track.

In the Data Science: Wrangling course by edX a piece of our Professional Certificate Program in Data Science, we cover a few standard strides of the information fighting cycle like bringing information into R, cleaning information, string handling, HTML parsing, working with dates and times, and text mining. 

Data Science: Wrangling certification is offered by the platform of edX in association with Harvard University. Professor Rafael Irizarry aims to provide the candidates with the skills and insights about Data Science and subjects associated through videos and discussion forums.

The candidates are provided with the online Data Science: Wrangling certificate with the signatures of the instructors on it. Data Science: Wrangling classes being a self-paced course offers flexibility to its candidates to learn at their own pace and comfort. Among the two tracks, the candidates will be able to choose either the verified track or the audit track. In the audit track, the candidates will be able to learn and complete the course within a limited period. Again, on the other hand, the students will be learning the course for an unlimited period.

The candidates can also opt for an associate programme on Data Science offered by edX again for a better understanding and in-depth knowledge about the subject along with Data Science: Wrangling training. 

Data Science: Visualization certification course is an introductory course about data science. The topics it covers are the basics of data visualization and data analysis. This course includes case studies on global health, economics, and trending diseases in the United States. This course is a part of the professional certificate programme. Data Science: Visualization training entails looking at mistakes, biases, and many other systematic errors in data that need special care. It is very difficult to spot mistakes within a dataset, for that matter, it is particularly important. 

Data Science: Visualization online course is verified by one of the leading institutions of the world, Harvard University. The courses offered by edX offer financial assistance to economically weaker sections. A 90% financial assistance will be offered to those who fit the criteria. The candidates will be able to access the course materials only for a specified period when it comes to learning in the audit mode. Again, in the verified mode, the candidates will be able to access the course materials for an unlimited time period.

The Data Science: Visualization classes program is shareable on all platforms. The enrollees can add it to their CV or resume. The digitisation of the modern world has led to growing demands for data visualization. Through Data Science: Visualization training, the enrollees will be able to access profitable skills for future careers that will be based on data visualization.

Measurable deduction and displaying are vital for investigating information influenced by some coincidence, and hence basic for information researchers. In the Data Science: Inference and Modeling certification course, you will become familiar with these vital ideas through a spurring contextual investigation on political decision gauging. 

Data Science: Inference and Modeling certification course will show how derivation and demonstrating can be applied to build up the factual methodologies that make surveys a powerful apparatus and we'll tell you the best way to do this utilizing R. Students will learn ideas important to characterize evaluations and edges of mistakes and figure out how you can use these to make expectations moderately well and give a gauge of the exactness of your estimate. 

When candidates gain proficiency with this, they will have the option to comprehend two ideas that are universal in information science: certainty stretches, and p-values. At that point, to comprehend articulations about the likelihood of an up-and-comer winning, candidates will find out about Bayesian demonstrating. At long last, toward finishing the Data Science: Inference and Modeling training, Harvard University will assemble everything to reproduce a disentangled adaptation of a political race conjecture display and apply it to the 2016 political race. 

The course is self-paced but the candidates need to select anyone from the audit or the verified track. There are two basic differences between the two tracks. In the audit track, the candidates get only a limited period of access to the course materials without having to pay any money. Again on the other hand the candidates who choose the verified track get unlimited access for viewing and learning the course materials.

The Principles, Statistical and Computational Tools for Reproducible Data Science course has been meticulously created keeping in mind the wide usage and huge importance of reproducible research across various disciplines. The Principles, Statistical and Computational Tools for Reproducible Data Science certification thoroughly covers all the fundamentals of reproducible science in a very lucid manner and adds on to various useful computational tools, thus appealing to a very wider audience in various fields like data science, bioinformatics, biostatistics, computational biology etc. 

The 8-week self-paced Principles, Statistical and Computational Tools for Reproducible Data Science classes are the perfect blend of video lectures, case-based studies and computational tools and can act as an asset to the knowledge of reproducible science of the candidates. Various intricate nuances such as data provenance have also been thoroughly explained in the course material. The best practices prevalent in pattern designing are also shared with the candidates. The Principles, Statistical, and Computational Tools for Reproducible Data Science online course encourages the candidates for peer-to-peer engagement for a great network and also acts as a place for intellectual and intense discussions on the topic.

There are two pathways in which enrolling in this course of edX is possible. One is the verified track, and the other is the audit mode. During the audit mode, the candidates shall have limited time access to the course, but access becomes unlimited during the verified track.

The participants can register and learn the difficult concepts and topics in the theory of probability. The basics of probability have been well cleared by experts at every point in the Data Science: Probability online course.

The Data Science: Probability certification syllabus comprises assignments, exams, and projects at the end of every concept. Different important concepts such as variables, and standard errors have been well taught in Data Science: Probability training. To understand the foundation, the basic terms will be cleared in the initial phase followed by the complexity in the next level.

At the end of the Data Science: Probability programme, the candidates will get certificates that help them stay motivated. The candidates can share it or add it to their resume. Adding it to the resume or CV helps them get better jobs or hike in the salary. The process of learning in the Data Science: Probability online certification is so clear that the candidates will have a firm understanding of the topic. There are 2 pathways to enroll in the course, one is the verified track, and the other is the audit mode. During the audit mode, the candidates shall have limited time access to the course, but access becomes unlimited during the verified track.

Data science is the study of using machine learning techniques and statistics to analyse raw data and find patterns and information. Several industries use it to make better business decisions, and researchers employ it to test out models or theories. The Data Science for Engineers programme will explore two main concepts, Big data and Data Science. 

Data Science for Engineers certification syllabus has been designed in association with NPTEL and IIT Madras. Professors Raghunathan Rangasamy and Shankar Narasimhan will teach the course, which aims to introduce participants to programming language R, familiarise them with mathematical foundations for data science, study data science algorithms, and provide practical knowledge using case studies. 

Data Science for Engineers training is an eight-week online course with the option to obtain certification. Candidates will have to submit periodic assignments and appear for an end-of-term offline exam to qualify for certification. Furthermore, organisations like Honeywell, Gyan Data Pvt. Ltd., Ford, and ABB, recognise this programme, and thus, learners can seek job profiles in similar industries. 

The Data Science Tools certification course from IBM provides you with a background on popular data science and data visualisation tools, including RStudio IDE, Jupyter Notebooks, and Watson Studio. Learn about the proper usage of each tool and how data scientists utilise these tools today. You will also get to understand what programming languages the data science tools can execute and what limitations and features they possess. 

The seven-week-long Data Science Tools programme is introductory and belongs to the Data Analysis and Statistics domain. Besides, the tools will be hosted in the cloud, and you will learn to follow instructions and test the tools to run simple code in R or Python. For finishing the training, you will complete a final project on IBM Watson Studio with a Jupyter Notebook on Cloud.

Moreover, you must demonstrate your expertise in writing Markdown, preparing a notebook, and sharing your work with peers. This hands-on Data Science Tools training will familiarise you with some of the most in-use, greatest, and latest data science tools. The course curriculum, divided into six modules, allows you to learn through lab sessions, assignments, graded quizzes, practice exercises, and more.  

Learners may choose any track from the two mentioned ones: audit and verified. These tracks are self-paced and offer limited and unlimited accessor audit and verified tracks respectively.

Spatial Data Science and Applications certification course is a specialized course for the learners seeking for understanding Data Science and its applications. Programming and analysis are needed everywhere. Every big company today needs employees with skills to operate analysis related to data structure and the study of the whole data format. 

Such need and study have brought a new requirement in today’s operating market which helps in gaining necessary information about various aspects of data structure. Topics like DBMS, SDBMS, HDFS and others are explained thoroughly under this course. With flexible deadlines, this Spatial Data Science and Applications online course is a one-stop destination for the learners seeking proper knowledge under this course. 

The duration of Spatial Data Science and Application training course is 6 weeks and is available for the learners with a genuine interest in the subject. 

In the Introduction to Data Science online course, the students will be getting to learn about the importance and applications of data science and the use of algorithms in it. The course has been designed for six weeks. The online programme on Introduction to Data Science training by edX will be digitally hosted and covered by IBM. 

Imparted by data scientists, this programme will require 3 to 6 hours per week of study. This Introduction to Data Science classes program covers a span of topics that will enable candidates to learn about data science, tools, algorithms and other elements utilised in a business scenario. The programme is pursued online wherein the candidates can enrol as per their convenient schedule. 

Since the programme is taught by data practitioners, candidates will gain the opportunity to learn the importance of data science in present times and in times to come. A most sought-after programme, candidates can also take up other associated programmes such as Data Science Foundations, IBM Data Science and Essential Technologies for Business. Candidates will find 2 tracks to enrol into and finish learning the programme. One is the audit track and the other is the verified track. These tracks can be learned based on one's own schedule but the audit track gives limited access whereas the verified track gives unlimited access to the course materials.

Materials Data Sciences and Informatics is an intermediate-level course ventured jointly by the Georgia Institute of Technology and Coursera. The system is a flexible one that allows the learners to pursue it in the online mode at their own pace and time.  Materials Data Sciences and Informatics Certification Course, offered by Coursera, can be taken by non-English speaking learners too as the subtitles are provided in the languages of, Portuguese (European), Spanish, French, and Russian. 

Materials Data Sciences and Informatics Certification by Coursera is all about the nascent discipline of Materials Informatics that is part of computational, material, and information science. The learners can complete the certification programme within the minimum duration of 9 hours. They can make a deep understanding of data science, informatics, data science in materials science, biomedical informatics and data science, statistics, and the like. 

We live in a world driven by data, and through the Introduction to R for Data Science course, you can learn how to make the most of it using the R platform. This programme will take you through the various essential concepts of R, starting from how to download, install, and run the platform on your machine. 

During the Introduction to R for Data Science online course, you will work with airline data and learn how to manage data using R. This is an introductory programme in R and data science, created for beginners who want to pursue this field and gain the foundational knowledge. Purdue University, USA, has developed this Course which is entirely free of cost on Future Learn.

If you want to study more advanced concepts and theorems of data science and R, then the Introduction to R for Data Science programme by Future Learn will be the perfect beginner course for you. Moreover, you can avail of this module for free or choose to pay for upgraded services and enjoy enhanced benefits by Future Learn. 

The Introduction to Process Mining with ProM course is being imparted by FutureLearn to provide the learners an understanding of process mining. This course has been developed by Eindhoven University of Technology, it is a design-oriented and research-driven university of technology. Process mining integrates business process management along with data science.

Taking the Introduction to Process Mining with ProM classes will teach the participants how to use a free, open source process mining framework to visualize, analyze, and improve processes based on data. 

Participants will be able to visualize and analyze business operations based on the recorded event data of their logs.  By pursuing the online Introduction to Process Mining with ProM certification programme will develop a critical and a process-centric perspective towards data, which is not possible in case of machine learning techniques or classical data mining. The Introduction to Process Mining with ProM syllabus has been designed in a manner that will develop proficiency in various process mining techniques such as social network analysis, conformance checking and performance analysis. Learners will be equipped to analyze the usage of public transportation by people, substantiate whether the bank loan application process is executed correctly, assess the learning behavior of students in a MOOC for course contents improvement and to predict when hardware parts are likely to break down.

The  Process Mining in Healthcare course by Future Learn is a special course that teaches all about the process of mining and gives a detailed study and explanation for students.

The students will obtain various skills and techniques of process mining such as analyzing healthcare data, improvising, using the ProM lite tool, event log filtering, event log inspection, and so on. The duration of the Process Mining in Healthcare classes are four weeks. By the end of the fourth week, students will gain plenty of knowledge and skills in process mining. The curriculum is designed by professionals in such a way that every topic is covered in these four weeks without any rush.

This Process Mining in Healthcare certificate course is developed by the Eindhoven University of Technology which is a prestigious research-driven university of technology. The Process Mining in Healthcare syllabus is designed by the universities which let the students have in-depth learning and understanding about the concepts. The professors taking the Process Mining in Healthcare classes are highly-trained and experienced in the subject who are from popular universities. It is an online course where students can learn from the comfort of their homes. Overall, it is such a well-designed course that creates an opportunity to study process mining. 

Also Read: Introduction to Process Mining with ProM

The Data Science Ethics certification course focuses on the learning of working with privacy ethics, data sharing and algorithmic decision-making. As patients, we worry for the safety of our medical records; but as patients, we still expect to benefit from the review of the evidence in the medical records. As people, we want a fair hearing before we are convicted for a crime; but as citizens, we want to deter the terrorists before they attack us. As a moral choice, we appreciate the recommendations we get from data-driven algorithms in the Data Science Ethics by edX; but as decision-makers, we are still worried about unintended bias. Often data scientists master the instruments of commerce and get to work straight away, without appreciating the real implications of their work. 

This Data Science Ethics online course focuses on ethics directly relevant to data science and provides you with a context for examining these questions. This concept focuses on ethics, which are common principles that tend to discern right from wrong. Ethics were not the rule, but they were generally the foundation of the law. The learners can pursue the programme in two varied tracks; verified and audit track. In the verified track, the learners will get unlimited access and a certificate. In the audit track, they will get access to the course for a limited duration. 

In the online course on SQL for Data Science classes program emphasis is given on the domain of database and real-world application. In the course, the students will be working on the database files, datasets and real data science tools. The SQL for Data Science certification syllabus will be covered within a time frame of four weeks. Industry experts and practitioners will be guiding the students throughout the programme. 

SQL or Structured Query Language programme will enable candidates in learning about using this language in extracting data types and communicating with the database. This SQL for Data Science training course by edX is pursued with an intent to get introduced to the concepts of relational databases as well as learn, pursue and implement the basic knowledge and understanding of SQL language. The candidates will get exposure to practical learning which will make it simple and easy to learn about this language. The programme will require 2 to 4 hours of weekly study. 

Candidates will find 2 tracks to enrol into and finish learning the programme. One is the audit track and the other is the verified track. These tracks can be learned based on one's own schedule but the audit track gives limited access whereas the verified track gives unlimited access to the course materials.

This course will educate candidates on the significance of data science in boosting data-driven innovation in businesses. The Data Science for Business Innovation certification programme has been developed to teach central data science concepts, including machine learning, data communication, big data and data valorisation. 

The Data Science for Business Innovation online course by Coursera also sheds light on Data Science’s tools and techniques, success stories, terminology, use cases and various applications. You will also explore its more technical aspect by learning about semi-supervised, unsupervised and supervised techniques. Furthermore, the distinctions between prescriptive, predictive and descriptive analytics will be discussed.

The Data Science for Business Innovation syllabus covers important topics such as regression, clustering and classification methods. Also, you will study data analysis, pros and cons of different machine learning methods, data needs and practical applicability issues. With the help of this course, you will understand the roles and impact of NoSQL data models and scalable cloud-based computational platforms.