NEWSLETTER
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It can be difficult to begin a new learning journey when you have little or no experience or even understanding of which path to follow. Do you take a boot camp? But maybe you can't commit to time constraints. Do I go back to university? But that's a considerable cost that many people are not willing to bear. How about online courses where you can learn at your own pace and without hurting your pocket?
This blog is aimed at beginners looking to transition into the world of data science. A world that becomes more popular every day. Although these courses provide details on how long it will take you to complete them based on the hours you put in, I truly believe that the more committed you are, the faster you will be able to complete the course.
You can complete all of these courses in one year if you commit to it!
Link: Google Data Analytics Professional Certificate
A course that is very popular for those in the world of data science. I have personally taken this course and I think it is one of the best courses for any beginner! This course will take you 6 months to complete if you spend 10 hours a week. I was able to complete it in a month because I had free time and was able to do it faster!
Consisting of 8 sections, this course will delve into daily data usage, best practices, and processes for your new data analytics job. You will learn how to clean and organize data for the analysis process and perform calculations using spreadsheets, SQL programming and R. It doesn't stop there, you will improve your analytical skills by creating data visualizations and also learning about tools like Tableau.
At the end, you'll earn a certificate and also have exclusive access to career resources, such as resume review, interview preparation, and career support.
Link: IBM Data Science Professional Certificate
Go one step further and take your analytics skills to the next level with a professional certificate in data science from IBM. With no experience required, you can complete this course in 5 months if you dedicate 10 hours a week. Remember, the more hours you put in, the faster you can complete the course.
In the course, you will learn the most up-to-date skills and practical knowledge that data scientists use in their daily tasks. You'll dive into learning about tools, languages, and libraries like Python and SQL, which are very popular. Not only will you learn how to clean data, analyze it, and then visualize it. You'll also learn how to create machine learning pipelines and models.
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 interviews.
Link: Specialization in machine learning
Considering how things are moving right now and chatbots are the hot topic, having machine learning under your belt is more important than ever. This beginner course is offered by Stanford University and DeepLearning.ai was created to help people enter the world of ai. You can complete this course in 2 months if you dedicate 10 hours a week.
This course will help you master the basics of ai and have practical machine learning skills under your belt. Learn how to build machine learning models with NumPy and scikit-learn, such as supervised models for prediction. You will also learn how to build and train a neural network with TensorFlow. Decision trees, ensemble methods, clustering, anomaly detection, deep reinforcement learning – this course has it all!
Link: Specialization in deep learning
DeepLearning.ai offers another course where you will go from a machine learning beginner to an expert. This course is continually updated with cutting-edge techniques to help you enter the world of ai and will take you 3 months to complete if you spend 10 hours a week.
Learn how to build and train deep neural networks, as well as identify key architectural parameters. You will also learn how to use standard techniques and optimize algorithms to train/test and analyze deep learning applications. You will build a convolutional neural network (CNN) and apply it to detection and recognition tasks, where you can use neural style transfer to generate artistic content. Great, right?
When it comes to learning something new, we often find ourselves overcomplicating the learning process. With these 4 courses, you can go from beginner to expert before the end of the year.
But it's important to remember that the data science industry is always about learning, so make sure you're prepared to learn new things as they arise. If you're considering generative ai more as one of your goals, take a look at DataCamp's 5 best courses to master generative ai.
nisha arya is a data scientist and freelance technical writer. She is particularly interested in providing professional data science advice or tutorials and theory-based data science insights. She also wants to explore the different ways in which artificial intelligence can benefit the longevity of human life. A great student looking to expand her technological knowledge and writing skills, while she helps guide others.
