Top 10 Data Science MOOCs for Aspiring Scientists to Gain Accuracy

Top 10 Data Science MOOCs for Aspiring Scientists to Gain Accuracy

Data science MOOCs enable students to gain domain knowledge in a flexible and efficient manner

Data science offers tremendous career opportunities to aspiring techies. The demand for skilled and talented data scientists is high, salaries are getting competitive, and the perks are numerous. The significance of data-driven decision-making is now realized by organizations around the world. Meanwhile, to provide for the growing demands of skilled data scientists, institutes and universities around the world have decided to offer advanced data science courses, both in the online and offline form to ensure that aspiring techies can pursue this evolving domain and contribute to the development of the tech ecosystem. Quite similarly, online education providers have introduced data science MOOCs. MOOCs are basically free online courses available for anyone to enroll in. They are affordable and flexible means to learn new skills. Various edtech domains are offering MOOC courses to enable students from any level of the domain to acquire skills in any other field. Here, we have listed the top 10 data science MOOCs that students can enroll in 2023 to ensure a secure future in the domain.

Statistical Inference and Modeling for High-Throughput Experiments

Offered by: Harvard University on edX

In this course, students will learn various statistics topics including multiple testing problems, error rates, error rate controlling procedures, false discovery rates, q-values, and exploratory data analysis. It also focuses on introducing statistical modeling and how it is applied to high-throughput data. With the help of several examples of how these concepts are applied in next-generation sequencing and microarray data, it offers itself as one of the best data science MOOCs in 2023.

High-Dimensional Data Analysis

Offered by: Harvard University on edX

This program is perfect for students interested in data analysis and interpretation. It starts with learning the mathematical definition of distance and using this to advance the use of the singular value decomposition (SVD) for dimension reduction and multi-dimensional scaling and its connection to principal component analysis.

Case Studies in Functional Genomics

Offered by: Harvard University on edX

This program explains how to perform the standard processing and normalization steps, starting with raw data, to get to the point where one can investigate relevant biological questions. Throughout the case studies introduced in the course, students can make use of exploratory plots to get a general overview of the shape of the data and the result of the experiment.

Data Processing Using Python

Offered by: Coursera

This course is based on financial data. Through the establishment of popular case studies, learners can more vividly feel the simplicity, elegance, and robustness of Python. Also, it discusses the fast, convenient, and efficient data processing capacity of Python in humanities and social sciences fields like literature, science, engineering, and business fields.

Foundations of Data Science: K-Means Clustering in Python

Offered by: Coursera in Partnership with the University of London

This MOOC is designed by an academic team from Goldsmiths, University of London. It will quickly introduce the participants to the core concepts of data science to prepare them for intermediate and advanced data science courses. It focuses on the basic mathematics, statistics, and programming skills that are necessary for typical data analysis tasks.

Data Science Math Skills

Offered by: Duke University through Coursera

This course is designed to teach learners the basic math they will need in order to be successful in almost any data science math course and for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science math skills introduce the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one at a time.

Data Science Foundations

Offered by: Great Learning

The Data Science Foundations course proffers the participant's knowledge on the introduction to the subject and gives them insights into the different phases of its life cycle. The course covers topics about various tasks carried out in data science and different programming languages that are compatible to work with to accommodate the tasks efficiently.

Measures of Central Tendency

Offered by: Great Learning

This course intends to cover central tendency concepts for data science. It basically begins with helping them understand the importance of statistics. It then continues with topics such as types of statistics and data, then elaborates on central tendency and measures of dispersion, providing a perfect base for aspiring data scientists to connect with the fundamentals of data science.

Introduction to Data Science Specialization

Offered by: IBM in partnership with Coursera

This specialization will introduce the students to what data science is and what data scientists do. They'll discover the applicability of data science across fields, and learn how data analysis can help make data-driven decisions. Besides, the course will enable them to kickstart their career path in the field without prior knowledge of computer science or programming languages.

Intro to Data Science

Offered by: Udacity

The class will focus on breadth and presentation of the topics briefly instead of focusing on a single topic in depth. This will give you the opportunity to sample and apply the basic techniques of data science into real-life situations.

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