Data-Science

7 Best Data Science Courses for Aspiring Data Scientists

In this era, where online learning platforms offer an abundance of courses, it is hard for one to choose the right one among them. In this article we will provide a curated list of 7 best data science courses that will provide you with valuable insights and opportunities that are worth exploring.

IBM Data Science Professional Certificate:

The IBM Data Science Professional Certificate is an online program offered by IBM. This program is tailored to help aspirants of data science or machine learning who have little or no experience in computer science or programming. This certification allows participants to garner insights using real data science tools and enable them to work with real-world data sets through IBM Cloud. The program consists of nine online courses including open-source tools and libraries, Python programming, databases, SQL, data visualization, data analysis, statistical analysis, predictive modeling, and machine learning algorithms. Upon completion of the program, participants receive a digital badge from IBM.

Python for Data Science and Machine Learning:

Featured on the Udemy platform, this course not only covers fundamental concepts but also delves into advanced data visualization techniques using libraries such as Matplotlib and Plotly. By mastering these, aspirants will be able to create captivating and effective visualizations. In this course, you can garner knowledge about machine learning algorithms like Random Forests and Decision Trees. Topics covered in the course range from web scraping and connecting Python to SQL to machine learning and natural language processing (NLP).

Business Analytics Specialization:

Facilitated by University of Colorado Boulder this course is designed for intermediate level aspirants. The primary focus of this certification is practical data analytics techniques. With the help of this course, data science aspirants can work on business growth. Key aspects of this certification include conceptual models of business and basic database models. The course also equips participants with proficiency in using tools like Excel and Analytic Solver Platform.

Advanced Analytics for R in Data Science:

This course is also designed for beginner level aspirants who want to improve their skills in R programming and R Studio. It offers a variety of learning objectives, including how to prepare data for analysis in R, perform the median imputation method, and work with date-times. The course is available on the Udemy online learning platform.

Google Data Analytics Professional Certificate:

The Google Data Analytics Professional Certificate on Coursera is designed to provide essential skills for entry-level data analytics roles. People having little or no experience, both can opt for the course. The duration of the certification is less than six months. Upon completion, you can apply for roles like junior data analyst or database administrator. The program includes interactive content and assessments that covers skills such as data collection, visualization, problem-solving, SQL etc.

SQL for Data Science:

This course provides participants knowledge about the fundamentals of SQL, practical experience in manipulating data and helps them to create new tables and transfer data between them. Throughout the course, students will be acquainted with common SQL operators and learn how to merge data from different sources. The curriculum also covers advanced topics like case statements, data governance, and profiling. This course is available in Coursera.

Harvard Professional Certificate in Data Science:

This professional certification course, offered by Harvard University on the edX platform, is designed to elevate your data science skills to an advanced level. It focuses on the practical implementation of machine learning (ML) algorithms and provides a deep understanding of fundamental data science concepts. Throughout this course, participants will be trained to develop R programming skills and will be introduced to statistical concepts.Additionally, learners will be acquainted with critical tools used by data scientists, such as Unix/Linux, Git, and RStudio.