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Starting a recent educational path can be tough if you have no experience or even don’t know which path to take. Are you attending boot camp? But maybe you can’t commit to time limits. Will I go back to university? But this is a huge cost that many people do not want to afford. How about online courses where you can learn at your own pace and not burden your back pocket?
This blog is aimed at beginners who want to enter the world of data science. A world that is becoming more and more popular every day. While these courses come with detailed information on completion time, based on the number of hours you put in, I truly believe that the more you put in, the quicker you will complete the course.
If you put in the effort, you can complete all of these courses in a year!
To combine: Google Data Analytics specialist certificate
A very popular course among data scientists. I have personally attended this course and I think it is one of the best courses for any beginner! It will take you 6 months to complete this course if you devote 10 hours a week. I managed to complete it within a month because I had free time and managed to do it faster!
This 8-unit course will introduce you to the everyday exploit of data, best practices, and processes in your recent data science job. You will learn how to neat and organize data for the analysis process and make calculations using spreadsheets, SQL and R programming. That’s not all, you will develop your analytical skills by creating data visualizations and learning tools such as Tableau.
At the end, you will receive a certificate and have exclusive access to career resources such as resume review, interview preparation and career support.
To combine: IBM Data Science Professional certification
Go a step further and take your analytics skills to the next level with a Data Science Specialist certification from IBM. With no experience required, you can complete this course in 5 months if you devote 10 hours a week. Remember, the more hours you devote, the faster you will complete the course.
During the course, you will learn cutting-edge practical skills and knowledge that data analysts exploit in their everyday tasks. You will delve deeper into tools, languages and libraries such as Python and SQL that are very popular. You will learn not only how to neat data, analyze it and then visualize it. You’ll also learn how to build machine learning models and pipelines.
Take the skills you learn in this course and apply them to real-world projects and build a portfolio of data projects to show off in job interviews.
To combine: Machine learning specialization
Given current developments and chatbots being a sizzling topic, having machine learning under your belt is more significant than ever. This beginner-friendly course is offered by Stanford University and DeepLearning.AI, which was created to aid people enter the world of artificial intelligence. You can complete this course in 2 months if you devote 10 hours a week.
This course will aid you master the basics of artificial intelligence concepts and gain practical machine learning skills. Learn how to create machine learning models with NumPy and scikit-learn, such as supervised models for prediction. You’ll also learn how to build and train a neural network using TensorFlow. Decision trees, ensemble methods, clustering, anomaly detection, deep reinforcement learning – you’ll find it all in this course!
To combine: Deep learning specialization
The next course is provided by DeepLearning.AI, which will take you from a machine learning beginner to an expert. This course is constantly updated with cutting-edge techniques to aid you break into the world of artificial intelligence. It will take you 3 months to complete this course if you devote 10 hours a week.
Learn how to build and train deep neural networks and identify key architectural parameters. You’ll also learn how to exploit standard techniques and optimize algorithms to train/test and analyze deep learning applications. You’ll build a convolutional neural network (CNN) and apply it to detection and recognition tasks, where you’ll be able to exploit neural style transfer to generate artistic content – frigid, right?
When it comes to learning something recent, we often find that we overcomplicate the learning process. With these 4 courses, you can go from beginner to expert before the end of the year.
However, it’s significant to remember that the data science industry is always about learning, so make sure you’re prepared to learn recent things as they arise. If generative AI is one of your goals, check out DataCamp’s top 5 courses for improving your generative AI.
Nisha Arya is a data scientist, freelance technical writer, and editor and community manager of KDnuggets. She is particularly interested in providing career advice or tutorials in data analytics and theory-based knowledge in data analytics. Nisha covers a wide range of topics and wants to explore the different ways in which artificial intelligence can impact the longevity of human life. Nisha is an avid learner and strives to expand her technical knowledge and writing skills while helping others.