Top 10 Data Science Courses to Upskill Yourself This Recession

Recession Pities no one. But you could save yourself with these Data Science Courses

Data Science is definitely changing the world! From being one of the highest paying jobs to helping the companies make better decision, Data Science is everywhere. Recession pities no one, but you could save yourself if you upgrade your data science journey with these Data Science Courses. Here are some of the top Data Science Courses to upskill yourself this recession.

Specialization in Data Science- JHU @ Coursera

One of the most popular and highly rated course collections on this list is this one. Overall, the R programming language and the Data Science specialisation provide the perfect balance of theory and application. This course covers a wide range of data science intricacies. This course is one to look forward to because it features a whole part devoted to statistics.

Applied Data Science with Python Specialization — UMich @ Coursera

This outstanding specialisation, which focuses on the applied aspect of data science, is offered by the University of Michigan, which also offers an online Master's degree in data science. As a result, you'll learn how to use tools like matplotlib, pandas, nltk, scikit-learn, and networkx as well as other widely used data science Python libraries.

Consider the Statistics with Python Specialization first if your statistical knowledge is rusty. Many of the most crucial statistical techniques required for data science will be taught to you.

Data Science and Machine Learning Program (Scaler)

This custom-made Data Science and Machine Learning programme from Scaler – InterviewBit, developed with input from advisors at top 50 tech organisations, is regarded as one of the most well-liked online courses in the field. This programme gives you the chance to work on actual projects while getting immediate feedback from professionals in the field. You will be equipped to take on the most difficult Data Science and Machine Learning issues as well as real-world business initiatives thanks to the well-structured modules and practical practise. On this list, it is one of the most popular and highly rated courses.

Data Science  Advanced Program-IIM Calcutta

Students learn many methods and tools for handling, managing, analysing, and interpreting data in this curriculum. It is intended for working professionals who are eager to get practical experience handling and evaluating data. This course introduces students to learn about tools including SPSS Modeler, Oracle SQL, Tableau, Python, @Risk, R, Hadoop, Arena, and more while primarily concentrating on data management and analysis. The students will have a strong foundation for using advanced statistics and quantitative tools to make well-informed judgments after finishing the curriculum.

Professional Certificate in Data Science -Harvard University

Students can gain the information and abilities necessary to handle data analysis-related real-world difficulties through this curriculum.

It will offer you an advantage in your work as a data scientist by teaching you R programming, machine learning, and other topics through the use of real-world case studies.

You'll also learn how to use ggplot2 for data visualisation, dplyr for data manipulation, R programming, and Linux file management.

This curriculum consists of nine flexible and reasonably priced courses.

You'll be prepared to work independently on a data analysis assignment once you've finished this programme.

 Data Science Specialization – Johns Hopkins University

You will learn about all the topics and tools you will need for your data science journey in this course.

You will use the knowledge you have gained from working with actual data to develop a data product on display in your final capstone project.

You should have some programming knowledge (it need not be in R) and a solid grasp of algebra as prerequisites.

Additionally, though it is not required, having a fundamental understanding of calculus and linear algebra may be useful.

After completing this course, students will have an impressive portfolio to show off their knowledge of the subject.

Intro to Data Analysis – Udacity

This self-paced course from Udemy is given by Caroline Buckley, manager of Ford Motor Company's intelligent customer interactions (ICI), and it may be finished in around six weeks.

The programme is a component of Udacity's Nanodegree in Data Analysis.

Beginner data analysts who wish to learn how to use data analysis tools should take this course.

Python programming experience and familiarity with terms like classes, objects, and modules are prerequisites for learners.

Tableau 2022 A-Z: Hands-On Tableau Training for Data Science- (Udemy)

This self-paced course from Udemy teaches students how to use Tableau to create a variety of data visualisations, including bar charts, maps, scatterplots, and interactive dashboards. It has 8.5 hours of on-demand video.

Additionally, by building data hierarchies, including filters, and using sophisticated data preparation tools in Tableau, students will learn how to prepare, organise, and analyse data.

Data Science: Machine Learning – (Harvard University on edX)

This Harvard University-developed course can be finished in 8 weeks at a rate of 2-4 hours per week and focuses on machine learning applications in data science.

The concept of training data and how to use a data set to find possibly predicative associations will be taught to the students.

Rafael Izirrary, a professor of biostatistics at Harvard University, is the instructor for the course.

Machine Learning Specialization – (Andrew Ng on Coursera)

This three-course curriculum teaches core AI and machine learning principles to novices and is provided by DeepLearning.AI and Stanford University.

Andrew NG, a pioneer in the development of self-learning machines and co-founder of Coursera and Google Brain, is the program's director.

The recommended pace for this course is nine hours per week, which can be finished in three months.