Edx Data Analysis Courses & Certifications

The Computing for Data Analysis Certification Course is brought by the online learning platform of the Georgia Institute of Technology, to provide advanced-level learning in the field of Computer Science. The course is a hands-on introduction to the part of analytics, combining both the fields of computer science and mathematics. 

A candidate will strengthen the foundations of data-intensive computing and numerical related to computing through the course. The programme is aimed at the candidate to develop a new process of thought regarding basic principles related to programming that will also assist them in practising relevant topics of modern data analysis and learning data mining. The learners can pursue the programme in paid or free audit mode. The paid mode will enable the learners to have unlimited access whereas the free audit mode will provide access only for a limited period. 

The Computing for Data Analysis training also teaches the data analysis pipeline and the concepts of machine learning including the pre-processing, storage, and analysis of data and figures. With the application of basic mathematical tools like numerical linear algebra and algorithms, the students learn how to handle data-intensive computing. The verified track of the course also includes graded assignments that’ll help in polishing the analytical knowledge of the student.

The Data Analysis for Social Scientists certification course will introduce learners to the fundamentals of statistics, probability, and data analysis. The curriculum covers most modern data analysis techniques including estimation, prediction, regression and econometrics, experimental design, A/B testing, randomized control trials, data visualization, and machine learning. 

All these concepts are illustrated using real-world examples. Candidates will also learn how to use the statistical package R, and perform self-directed empirical analyses.

The Data Analysis for Social Scientists certification is also a prerequisite for two independent MicroMasters programs that the Massachusetts Institute of Technology (MIT) offers: MicroMasters in Data, Economics, and Development Policy (DEDP) and MicroMasters in Statistics and Data Science (SDS). 

Before you apply to the Data Analysis for Social Scientists program, you check out the course preview to go through the content, exercises, etc. Some resources are also available if you are new to these subjects or wish to jog your memory. If you score 60% or more in the course preview, it indicates that you are prepared for this course. 

In the Data for Effective Policy Making certification course, enrolled candidates will learn to use, understand and analyze information. The course will help candidates improve their decision-making process using "growth statistics" and "Caribbean data gateway" platforms, which present data and socio-economic indicators from the Caribbean region and Latin America. 

After completing the course, the applicants will gain knowledge about tools for data navigation, simulation, and interpretation of visualization. They will also understand how to apply different types of data analysis based on the policies that are implemented. The course is built on real-life experiences to help students get an easy, realistic, and enjoyable understanding of various ideas and methods. Through various useful activities, candidates will learn to apply their acquired knowledge and use graphs and data. The self-paced programme can be taken in two different enrolment options; verified and free audit. In the free mode, they audit the course for a limited period. 

The Causal Diagrams: Draw Your Assumptions Before Your Conclusions training course by edX actively points out the different methods of using causal diagrams and how they are useful in many disciplines such as statistics, epidemiology, policy evaluation, sociology, psychology, and many more. Here, the implications of causal diagrams and also their limitations are shown.

The Causal Diagrams: Draw Your Assumptions Before Your Conclusions certification syllabus comprises seven guided lessons in its first part. In the lessons taught in the Causal Diagrams: Draw Your Assumptions Before Your Conclusions certification course there will be introductions to DAGs, SWIGs; their rules, and problems, and also about confounding. Case studies about the real implications of the Causal diagrams will also be shown in the Causal Diagrams: Draw Your Assumptions Before Your Conclusions programme. There are also provisions of 90 % financial assistance for the low-income grade participants. It is a self-paced online programme. The Causal Diagrams: Draw Your Assumptions Before Your Conclusions certification course is verified by Harvard University.

The Certificate can be accessed in the verified track. The participants can share the certificate on all platforms such as Linkedin. The certificate will fetch a good career option and also better connections in Linkedin. 

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 Image Processing and Analysis for Life Scientists program have been meticulously created considering the indispensability of image-based methods for life scientists. The Image Processing and Analysis for Life Scientists certification course thoroughly explains analysis methods using all the open-source solutions, leaving the candidates with the freedom of choosing commercial solutions as per their choice and convenience. Considering the evolution of light microscopy from sketched-out raw observations from the eye to high throughput multi-channel, multi-plane, multimode and multi-position acquisitions, which produce information-rich images easily quantifiable for answerability of biological questions, the course thoroughly teaches the learners how to adapt to all the rapid changes occurring and to maintain a sustainable workflow environment. 

The Image Processing and Analysis for Life Scientists online course thoroughly teaches the candidates the good practices and typical pitfalls that exist in the field of image analysis and empowers the candidates with a rigorous first-hand experience in image analysis through its carefully designed content. The candidates can take the course in verified or audit track. The audit track is free of cost and provides a limited period of access. 

Stochastic motion is the motion of particles like that of ink in water. As opposed to the movement of celestial objects which can be calculated, this motion cannot be predicted. The Stochastic Processes: Data Analysis and Computer Simulation certification course aim to introduce candidates to stochastic processes and how to conduct data analysis on them. 

Students will first learn the fundamental theories governing stochastic processes in the training programme. Then, using Jupyter (iPython) notebook, they will learn how to do numerical simulations and perform them. They will analyse the simulation data as well. The six-week-long  Stochastic Processes online course in Physics is made for students interested in thermal motion and particle motion. 

Faculty from the reputed Kyoto university in Japan teaches this course on Stochastic Processes: Data Analysis and Computer Simulation training by edX. Throughout this course, candidates will acquire knowledge of stochastic processes and programming. This online programme is completely free of cost. edX also offers a verified certificate upon course completion.

Learn how to derive insights from the noisy observations by enrolling in the Observation Theory: Estimating the Unknown certification. In research and teaching the TU Delft’s approach is a world-leading methodology for understanding the observations. This theory can be applied in every domain where the measurements shall be used to make an estimation of the unknown parameters.

The candidates will learn how to distinguish between the parameters and come up with the quality of results in Observation Theory: Estimating the Unknown training. Playing with noisy observations is one of the key takeaways for the candidates during this time duration of the course. The participants will learn how to validate the estimations and develop a systematic approach to dealing with real-life translations. The candidates will have real-world exposure to different models.

The learning process during the course will help participants know how the study of observations can help in better solutions. In terms of precision, a standardized approach to the parameters has been considered for the candidates. Most part of the course has been covered with examples, where the candidates will have better learning. The course also offers certification after the candidates successfully complete it if they choose the verified track and pay the course fee. In the free track, the students will get access to the course for a limited duration. 

The Deploying TinyML Certification Course is an open online course that introduces students to the steps involved in implementing TinyML applications. The course will help students understand the workings of the software along with the right codes required to deploy their tiny microcontroller-based device. It is a specialized course and a mix of computer science and electrical engineering.

The Deploying TinyML Training Course is an intermediate-level course that requires learners to have basic knowledge of the Applications of TinyML and Basic Programming in C/C++. The course taught in a self-paced manner will be beneficial for students who wish to earn a professional certificate in Tiny Machine Learning.

The Deploying TinyML Online Course is taught over 5 weeks with the aid of online course materials. The course is instructed by Vijay Janapa Reddi, Professor at Harvard University and Pete Warden, Technical Lead at Google. After the completion of the online assessment process, students will get access to a certificate in the paid verified mode. In the free audit mode, they can get a limited duration of access to the self-paced course. 

Data is an integral part of every field and is relevant to a large variety of audiences. Depending on your domain, you must know how to interpret, analyse and visualise data to your advantage. Unfortunately, most of us were never taught how to do so and cannot use data wisely. The Essentials of Data Literacy online course provided by edX is an attempt to help you build your data skills to accelerate your career.

The Essentials of Data Literacy course curriculum will take you through the different stages of the data lifecycle and teach you how to manage, analyse, and communicate with data. It is a four-week-long introductory programme that falls under the Data Analysis and Statistics domain. An offering by edX, this course has been designed by Davidson College to benefit a wide audience.

You can enroll in this course for free by taking up the audit track and setting a course goal for yourself. The audit track will give you free but unlimited access whereas the verified track requires some amount to upgrade and access the course for a lifetime. Moreover, after understanding the importance of data, you can earn an Essentials of Data Literacy certificate by paying the certificate fee. 

The High-Dimensional Data Analysis Certification Course is an advanced-level data science course that deals with the features of data analysis and data interpretation. The course will introduce students to extremely challenging cases relating to data analytics and discuss the usage of high-dimensional data sets.

The High-Dimensional Data Analysis Training Course offered by the edX platform is a self-paced course taught over 4 weeks. The course is delivered through online study materials under the guidance of Rafael Irizarry and Michael Love, professors at Harvard University.

The High-Dimensional Data Analysis Certification Syllabus would be beneficial for students who are planning to expand their knowledge base in topics like data visualization and data analysis of high-throughput data. Students who are interested in gaining knowledge about machine learning and data analytics can opt for the course. EdX provides two options for learners to pursue the self-paced programme, namely, verified and audit tracks. In the verified mode, the learners can get unlimited access to the programme and a certificate of completion. In the free mode, they can audit the course only for a limited duration.