Beginning a new learning journey when you have little to no experience or even knowledge about the path to choose might be challenging. Take a boot camp in Data Science, do you? Perhaps, though, you are unable to meet the deadlines. Should I return to my university? However, that comes at a high cost, which many individuals find unacceptable. What about taking affordable online classes that allow you to learn at your own speed?
Beginners wishing to make the switch to data science are the target audience for this blog. a universe that is only growing in popularity every day. I firmly think that the more hours you put in, the quicker you can finish the course, even if these courses have supplied information on how long they will take you to finish depending on the number of hours you commit.
If you put in the effort, you can finish all of these courses in a year!
Data Analytics
Link: Google Data Analytics Professional Certificate
a highly well-liked course among data science professionals. This is one of the greatest courses for beginners, in my opinion, having done it myself! If you put in ten hours a week, you can finish this course in six months. I finished it in a month since I had extra time and could work on it more quickly!
This eight-part course will cover best practices, procedures, and the everyday usage of data for your new career in data analytics. You will discover how to use spreadsheets, SQL, and R programming to do computations and clean and arrange data for analysis. Your analytical abilities will be further enhanced by making data visualizations and studying programs like Tableau.
Upon completion, you will get a certificate in addition to having first-hand access to employment-related tools including resume critiques, interview practice, and career counseling.
Data Science
Link: IBM Data Science Professional Certificate
With an IBM data science professional credential, you can go one step further and advance your analytical abilities. If you put in 10 hours a week, you can finish this course in 5 months without any prior experience. Keep in mind that you can finish the course more quickly the more hours you put in.
The course will teach you the most recent practical techniques and expertise that data scientists employ in their daily work. You will delve into the study of widely used tools, languages, and libraries like SQL and Python. You will get knowledge about data cleansing, analysis, and visualization in addition to other topics. Additionally, you will learn how to create pipelines and models for machine learning.
Create a portfolio of your data projects to present at interviews by using the skills you learn in this course for real-world tasks.
Machine Learning
Link: Machine Learning Specialization
Given the current situation and the widespread use of chatbots, having familiarity with machine learning is more important than ever. This is an introductory course offered by Stanford University and DeepLearning.AI was created to make it easier for people to enter the profession. You can complete this course in two months if you put in ten hours a week.
This course will provide you with a comprehensive overview of AI principles and useful machine-learning techniques. Discover how to use sci-kit-learn3, NumPy, and other machine-learning tools to develop supervised models for prediction. We will also discuss neural network creation and training using TensorFlow. Deep reinforcement learning, ensemble approaches, decision trees, clustering, and anomaly detection are all covered in this course.
Deep Learning
Link: Deep Learning Specialization
DeepLearning provides another course in the field in which you can become an expert in machine learning from a beginner. This course, which will take three months to finish if you put in ten hours a week, is updated frequently with cutting-edge methods to help you get started in the field of artificial intelligence.
Discover how to create and train deep neural networks and recognize important architectural elements. Additionally, you will learn how to train, test, and analyze deep learning applications using conventional methods and optimized algorithms. It sounds great, right? You will construct a convolution neural network (CNN) and utilize it for detection and identification tasks. Neural style transfer will allow you to create artistic content.
Concluding the discussion
We frequently find ourselves overcomplicating the learning process when we are learning something new. By the end of the year, you can go from being a beginner to an expert with these 4 courses.
However, it’s crucial to remember that learning is a constant in the data science field, so be ready to pick up new skills as they arise. Check out the Top 5 DataCamp Courses for Mastering Generative AI if learning more about this topic is one of your objectives.
