It’s a terrific moment to work as a data scientist, with plenty of job possibilities, high incomes, and exciting career prospects. But what if you’re a complete beginner? Fortunately, there are numerous possible learning paths. Other options for learning the skills required in the field include self-learning, joining boot camps, and earning a college degree. We’ll demonstrate how to progress from being a beginner to being job-ready in the field of data science in this article.
Is It Worth To Start Learning in 2023?
In 2023, it will be worthwhile to learn how to code, and it’s a really good idea. Your job prospects are increased by learning to code, and you gain knowledge and abilities that can be applied to your personal and professional growth.
This does not imply that everybody needs to learn how to code, though. Picking up coding is only a good idea if you have a genuine passion, or if you need it for your job or to advance your career.
Reasons for Learning to Code in 2023
- Learning to code is a very challenging hobby that calls for analytical thinking and problem-solving abilities.
- Knowing how to code can lead to a wide range of employment opportunities. Software engineers and developers are in high demand, thus developing this talent might increase your marketability and help you get your ideal position.
- Several degree and non-degree alternatives are available for learning to code. You can learn to code by enrolling in a boot camp, taking lessons online or in person, watching tutorials on YouTube and other learning platforms, or simply teaching yourself using online resources.
- Coding is a rewarding professional path with many advantages.
- Having coding skills can enable you to work on a variety of side projects and create your software, websites, or applications. This is a fantastic strategy to increase both your portfolio and your additional income.
Choose Online Data Science Tutorials For Beginners
1. Full Stack Data Science, AlmaBetter
This concentration includes Machine Learning, Deep Learning, Analytics Frameworks, Math for Data Science, Python for Data Science, and ML and Data Engineering. This data science tutorial emphasizes on data analysis as well as the soft skills required to become a data scientist, such as making inferences and asking appropriate questions.
2. Full Stack Web Development, AlmaBetter
The curriculum-driven, immersive courses offered by AlmaBetter. The curriculum for Full Stack Web Development is covered in this 30-week course. The topics covered in this module are Frontend Development, Backend Development, System Design as an Elective, and Advanced Frontend as an Elective.
3. Introduction to Data Science Using Python, Udemy
If you want to start from scratch, this is a great place to do so. The foundational information you should know is covered throughout the course, including what data science and machine learning are, what a typical day in the life of a data scientist looks like, and how the Python programming language fits into that framework.
4. Learn SQL, Codecademy
Before delving too further, would you like a general overview of SQL (another significant computer language used extensively in data science)? The free course offered by Codecademy is an excellent place to start learning the fundamentals.
Linear algebra is indeed crucial to data science. This course ought to accomplish the task in a day or two if you don’t want to return to school entirely.
6. Introduction to Machine Learning for Data Science, Udemy
This beginner-level course, which covers subjects like artificial intelligence (AI), machine learning, and computer science and teaches you how they all work together, can be finished in less than six hours. Although the website does provide a seven-day free trial, the fee could get quite high depending on how and when you choose to pay.
Also read: Some great ideas to rock the intros of your eLearning course
7. Supervised Machine Learning: Regression and Classification, Coursera
This is the ideal place to start if you want to learn data science in its entirety. This course, which is being taught by the co-founder of Coursera (yes, really), will delve deeply into machine learning—what it is, how it functions, and how you can use it in a data science career.
8. Data Science Foundations, Codecademy
Codecademy career paths are excellent for a variety of reasons. They start by researching deeply and systematically into a certain issue and then provide you with all the tools you require. They also assist you in applying your knowledge to real-world situations and practical tasks, which is helpful. You can even change to one of their more specialised career tracks for data scientists if you complete this course.
Data science is expected to experience some of the most significant advancements in the next ten years, thanks to the data explosion, the growth of the internet of things (IoT), and social media. Experts predict that over the next 10 years, the utility of computers and mobile devices will rise due to the emergence of machines. In addition, analysts predict that as people consume enormous volumes of online data, social media use will significantly rise. We think that the above-mentioned courses will enable those who are eager to learn data science to advance rapidly in their careers.