If you’re interested in learning how to do data science, we’ve put together a list of the top courses to help you learn more. We’ll talk about why data science is becoming so important, and how to get started if you’re looking to learn more about the field.
So, if you want to learn more about the subject, keep reading.
Udemy – Python for Data Science and Machine Learning Bootcamp
When it comes to data science, programming lies at its core. And the most popular programming language is Python.
Python has become one of the most popular programming languages in the world in recent years. It’s used in everything from machine learning to building websites and software testing which is why this course is the best for anyone looking to start a career in data science.
If you are looking to master data science and machine learning python libraries, then the Python for Data Science and Machine Learning Bootcamp is most definitely for you. Within this course you will learn how to use most of the popular Python machine learning and deep learning libraries like NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-learn, Meeshkan, TensorFlow, Keras, and more.
This course has been designed for both beginners with some programming experience and experienced developers looking to make the jump to data science! This means that no matter the level of knowledge you have, enrolling into this course will definitely open you up to the world of python profammign and data science as a whole.
Click here to enroll onto the Udemy – Python for Data Science and Machine Learning Bootcamp.
Coursera – Foundations using R Specialization by Johns Hopkins
This course covers all the foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in R, and conducting reproducible research.
R is an open-source programming language that is widely used as a statistical software and data analysis tool. It is available across widely used platforms like Windows, Linux, and macOS.
Within this course you can expect to learn how to:
- use R to clean, analyze, and visualize data.
- ask the right questions, obtain data, and perform reproducible research.
- use GitHub to manage data science projects.
- set up R, R-Studio, Github and other useful tools.
To take a closer look at Foundations using R Specialization by Johns Hopkins and enroll in it, you can click here.
MITx – MicroMasters® Program in Statistics and Data Science
This course is made up of four online courses and a virtually proctored exam that will provide you with the foundational knowledge essential to understanding the methods and tools used in data science, and hands-on training in data analysis and machine learning.
Machine learning is the study of computer algorithms that can improve automatically through experience and by the use of data. It plays a large role within the field of data science and artificial intelligence.
On this course you can expect to learn:
- the foundations of data science, statistics, and machine learning.
- how to analyze big data and make data-driven predictions through probabilistic modeling and statistical inference.
- how to identify and deploy appropriate modeling and methodologies in order to extract meaningful information for decision making.
- how to develop and build machine learning algorithms to extract meaningful information from seemingly unstructured data.
This course is one of the top data science programs available to complete data as it includes 5 graduate-level courses and will take around 1 year and 2 months to complete. It is also instructor-led and all the assignments and exams have specific due dates that need to be met in order to pass.
For more information about this MITx – MicroMasters® Program in Statistics and Data Science course click here.
Metis – Introduction to Data Science
This course is extremely highly rated by students and professionals alike, one of the main reasons being that it is taught live by a data scientist from a top company. It is a six-week-long data science course that covers everything in the entire data science process.
On this course you can expect to learn:
- Computer Science, Statistics, Linear Algebra Short Course
- Exploratory Data Analysis and Visualization
- Data Modeling: Supervised/Unsupervised Learning and Model Evaluation
- Data Modeling: Feature Selection, Engineering, and Data Pipelines
- Data Modeling: Advanced Supervised/Unsupervised Learning
- Data Modeling: Advanced Model Evaluation and Data Pipelines | Presentations
As this course is taught online and on a part-time schedule, it can fit flexibility into your lifestyle if you have other commitments that you cannot compromise. So if you have a strong desire to learn data science through top-quality instruction, a basic understanding of data analysis techniques and an interest in improving their ability to tackle data-rich problems in a systematic, principled way then this is the course for you.
The Metis – Introduction to Data Science provides structure and accountability to ensure you stay on track, finish strong, and achieve your desired outcomes. For more information on this course and to enroll in it, you can click this link.
MyDataCareer – Data Science for Beginners
If you are brand new to the world of data science and have got no idea where to start, then this is just the course for you. In this course, you will discover the types of problems, methods/techniques, and roles available in Data Science via examples and activities. You will also learn:
- Explanation of key concepts in data science: big data, data mining, libraries, datasets, API’s
- Programming languages and which ones to learn
- Data Science Methodology, expressed via Healthcare Insurance Company Case Study
- Experience The Power of Machine Learning and Natural Language Processing via Chatbot Example
- GitHub; how to use it for collaboration and version control.
One of the great aspects of this course is that there is no prerequisite, which means you can start even if you are hearing the term data science for the very first time.
To find out more about the MyDataCareer – Data Science for Beginners and enquire about enrollment click here.
Coursera – Deep Learning Specialization
If you are interested in finding out more about deep learning and exploring how it relates to data science and artificial intelligence, then this is the course for you. This foundational program will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.
By the end of this course you will be able to:
- Build and train deep neural networks, implement vectorized neural networks, identify architecture parameters, and apply DL to your applications.
- Understand complex ML settings and devise strategies to reduce errors.
- Build and train Recurrent Neural Networks and its variants (GRUs, LSTMs), apply RNNs to character-level language modeling, and work with NLP and Word Embeddings.
- Use best practices to train and develop test sets and analyze bias/variance for building DL applications, use standard NN techniques, and apply optimization algorithms.
If you have a background within this field and are looking to delve further into the world of data science, then click here to find out more about enrolling in the Coursera – Deep Learning Specialization course.
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