Edx 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-weeks long free online course. 

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 the 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 better understanding of the subject. 

The Data Science: Linear Regression classes programme is free to access for everyone. Although to get the verified certificate, the candidate must need to upgrade to the verified track. The Data Science: Linear Regression training is instructed by Rafael Irizarry, the professor of Biostatistics, Harvard University, with the aim 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.

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 at providing the candidates the skills and the 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 them. Data Science: Wrangling classes being a self paced course offers flexibility to its candidates to learn at their own pace and comfort. 

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 top 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 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 which 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 utilize these to make expectations moderately well and furthermore 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 the finish of 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 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 the peer-to-peer engagement for a great network and also acts as a place for intellectual and intense discussions for the topic.

The participants can register and learn the difficult concepts and topics in 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, projects at the end of every concept. Different important concepts such as variables, standard errors have been well taught in Data Science: Probability training. In order 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 which helps them keep 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.

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. 

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 of learning 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. 

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. 

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 are generally the foundation of the law.