Learn Data Science:

The Best Courses and Resources

If you want to pursue a career in data science, a great way to start is by enrolling in an online data science course. These online courses teach you the skills necessary to become a data scientist. You’ll learn data science topics such as data analysis, data science statistics, machine learning with Python, artificial intelligence, and data visualization.

Many of the best online data science courses teach using real-world scenarios. This will give you the knowledge and practical experience to succeed in the field. Read on to find out more about the best online data science and machine learning courses and resources.

What Is Data Science?

Data science combines programming skills, statistics, and data analysis. Data science aims to organize raw data and find actionable insights that can help organizations. It is increasingly used by businesses to uncover the best ways to engage their users and develop their services.

To find valuable insights, data scientists also store and analyze both unstructured and structured data sets. Although data science is closely related to computer science, there are stark differences between the two. Data scientists analyze all types of data to find business solutions, whereas computer scientists look more specifically at software and coding.

What Jobs Use Data Science Skills?

Many of the best tech jobs rely on data science skills. These include data scientists, machine learning scientists, data architects, and statisticians. Let’s look at how having data science expertise is essential to each of these careers.

Data Scientist

Data scientists use their data science skills to organize, clean and prepare, and analyze raw data. They usually work with what we call big data. Skills in programming languages like SQL and Python are vital for data scientists to do their jobs.

Data Architect

Data science enables students to learn how to mine, clean, and store data. Without these skills, data architects can’t create new database systems, analyze database systems, or optimize database systems.

Machine Learning Scientist

These experts heavily rely on the mathematical principles of data science. Machine learning scientists use data science skills to develop new algorithms for supervised and unsupervised machine learning tasks.

Statistician

Statisticians specialize in the mathematical and statistical side of data science. Using data science principles like data mining, data visualization, and data analyzing, statisticians can successfully perform their duties.

Steps to Learn Data Science

To learn data science, you need to start with the basics. You can continue to hone your skills through practice, short certificate courses, and connecting with peers in the industry. Below is a step-by-step guide on how to learn data science in 2021.

1

Take an Online Course

Nowadays, you don’t necessarily need a bachelor’s degree in data science to become a data scientist. Taking an online course or boot camp in data science is an ideal way to start on this career path. There are plenty of online courses and boot camps available to teach you the essentials of data science.

2

Learn Programming

Programming skills are essential to any career in data science. As well as honing your data science and data analysis skills, it’s worth gaining advanced knowledge of relevant programming tools. Find online courses and bootcamps in things like Python, R, and SQL.

3

Practice

After learning the fundamentals of data science, you need to practice what you’ve learned. Find a data science project for beginners to keep going over what you’ve learned.

Online assessments are also a great way to test your expertise. Data science is about practical skills, so practicing is important for data scientists.

4

Earn a Certificate

Once you feel more confident in your data science skills, it’s a great idea to attend a short data science certificate course. As well as helping you to develop your skills, you can show the certificate to future employers to demonstrate your learning. Make sure to choose a course based on your level of experience and the data science area you want to specialize in.

5

Network

Connecting with other data science students and professionals is vital, especially if you are new to the field. This will help you stay up to date with news from the industry. It’s also valuable in helping you overcome common data science problems.

Link up with your peers via data science forums, communities, or social media groups. Building a network of professional contacts will also be helpful when it comes to building your portfolio or work experience and finding a job.

The Best Courses to Learn Data Science

There are numerous online data science courses to help you find your dream job. You can choose to study the basics or specialize in machine learning or statistics.

Whatever your experience level and career ambitions, there’s an online data science course to suit you.

Level: Intermediate
Duration: Two to three hours
Cost: Varies
Outcome: Certificate of Completion

If you have some previous experience with Python and data science techniques, this course may work for you. The content covers how to accelerate Python productivity using PyCharm. You will learn the basics of PyCharm, the background of coding from hierarchies to running tests, and how to write better code.

Concluding this course, students will learn about debugging code and exploring data like R scripts and SQL queries. You can use their free ten-day trial, which gives you access to this course, a virtual library, real-world challenges, and a technology index.

Level: Intermediate
Duration: Six months
Cost: $4,000 upfront or $700 per month
Outcome: Certificate of Completion

This comprehensive online data science course by Explore covers SQL databases, Python, data visualization, and machine learning basics. You will also work on real-world challenges to build data algorithms using Python.

Explore offers student services too, like career coaching and a tried and tested job search framework to help you break into tech. To fund your studies, Explore offers a pay-as-you-learn option, as well as scholarships and student loans.

Level: Beginner
Duration: Five to 10 weeks
Cost: $3,250
Outcome: Certificate of Completion

BrainStation offers instructor-led, live classes to teach you the basics of data science. You will learn data modeling, data visualization, data cleaning, data analyzing, Python for data science, and machine learning. You will also participate in interactive assignments and complete a data science project.

The data science tools you will learn to use in this course are Python, Jupyter Notebooks, and Anaconda. You can pay for this course through upfront payment, installments, or employer sponsorship.

Level: Beginner
Duration: Two hours, 33 minutes
Cost: Free
Outcome: Certificate of Completion

Comprising 48 exercises and 15 video lectures, this data science online course is aimed at beginners. During the course, you will learn data science tools, how to build a live chatbot, cloud platforms, data pipelines, and data sources. This course also includes data preparation, data visualization, and A/B testing.

You will also have access DataCamp’s free online resources to help you learn data science. These include free assessments, webinars, white papers, e-Books, and tutorials.

Level: Beginner
Duration: Six weeks
Cost: Free
Outcome: Certificate of Completion (for $199)

Blending fundamental data science and machine learning concepts, this online course is tailored to beginners. Led by three instructors, this course covers regression and classification in machine learning, comparing machine models, and evaluating machine models.

Once you’ve completed this course, you’ll have an extensive understanding of the relationship between data science and machine learning. You can also receive a certificate on completing the courses, although you’ll have to pay for this.

Level: Beginner
Duration: One hour, 9 minutes
Cost: Varies
Outcome: Certificate of Completion

In less than two hours, students can learn data mining, data-driven decision-making, big data, deep learning, and machine learning. This online course by Pluralsight also looks at artificial intelligence. Students learn through on-demand video material. You don’t need any experience for this data science course.

Pluralsight offers a wealth of free resources to enhance your learning. These resources include blog articles, guides, podcasts, webinars, and virtual events. Pluralsight’s ten-day free trial allows you to complete this course for free.

Level: Intermediate
Duration: 68 hours
Cost: $549 for self-paced or $599 for full bootcamp
Outcome: Certificate of Completion

Simplilearn’s data science course teaches students about data analysis, machine learning, web scraping, and data visualization. There are four projects to complete during the course, which will give you valuable practical experience.

Students learn on Jupyter Notebooks. To broaden your skillset, this course also teaches data manipulation with Pandas, natural language processing with Scikit Learn, and data analytics. Once purchased, you will have lifetime access to this course.

Level: Beginner
Duration: 64 hours
Cost: $599 for self-paced or $699 for full bootcamp
Outcome: Certificate of Completion

If you want to know everything about R programming, you should consider this course from Simplilearn. There are ten real-world projects to complete in this course. You have lifetime access and can also access dedicated mentoring sessions to help you.

This course covers basic concepts like data structures, data clustering, regression analysis, statistics, and data analytics. You will also learn about the fundamentals of business analytics, which are extremely valuable skills for both data scientists and data analysts.

Level: Advanced
Duration: 2 weeks
Cost: Varies
Outcome: Certificate of Completion (for $79)

Are you not sure if you’re ready to take a full Master’s Degree in Data Science? This course is designed to help you decide and prepare. Students have the chance to explore the concepts covered in a data science master’s degree program like statistical thinking, privacy, ethics, and programming languages.

You will also cover data fundamentals, mathematics, and context and environment. Using Jupyter Notebook, you will learn artificial intelligence and Python. There is also a community of fellow peers you can interact with.

Level: Intermediate
Duration: 30 hours
Cost: Free to enroll, additional fees may apply
Outcome: Certificate of Completion

If you need to improve your skills in Python for data science, this introduction to data science course is for you. You will cover the fundamentals of a Python programming environment, lambdas, manipulating CSV files, and the NumPy library. Students will also learn about data cleaning, data structures, and data analysis.

This course is one of five courses in Coursera’s Applied Data Science with Python Specialization. After completing this course, 13 percent of graduates received a raise or promotion.

Level: Beginner
Duration: 2 weeks
Cost: Free, can upgrade for a fee
Outcome: Certificate of Completion

Through five hours of daily study over two weeks, students learn statistical analysis, machine learning, and basic data analysis techniques. You can also choose to take this course at your own pace.

The course includes video lectures, long and short-form articles, audio content, and exercises for practical experience. FutureLearn’s platform also creates an intuitive learning environment through assessments, progress pages, and progress notifications.

Level: Beginner
Duration: 2 weeks
Cost: $39 per month
Outcome: Certificate of Completion

Aimed at aspiring data scientists and analysts, this online course delves into statistics, machine learning, and data basics. Students will explore the best techniques for data sorting, filtering, and highlighting.

You will also learn about analyzing and visualizing data and the basics of statistical analysis. Students can also access assessments and quizzes to help them study. At the end of the course you’ll receive a certificate from this Microsoft-accredited course to show you have the industry-relevant skills.

Level: Advanced
Duration: Ten weeks
Cost: Free
Outcome: Certificate of Completion (for $350)

In ten weeks, students will learn about statistics, probability, mathematical theory, and machine learning. Using Jupyter Notebooks, you will gain hands-on experience by applying mathematical theory to data science problems. This course is suited to experienced students who want to specialize in the mathematical aspect of data science.

You can complete this online course at your pace. Unfortunately, there aren’t many student services offered in this course but it is taught by two professors from the University of California, San Diego.

Level: Beginner
Duration: Three months
Cost: $549 or $199 per month
Outcome: Certificate of Completion

Students will have lifetime access to this data science course from Skillcrush, and they can study at their preferred pace. You don’t need any prior experience for this course. During the course, you’ll learn how to use Slack, Repl.IT, and Chrome Devtools.

This course covers the basics of how to learn data visualization, HTML, SQL, Python, and statistical analysis. You will also learn about building web apps, data interpretation, control structures, data types, and computational thinking. There is an active Slack community of students for this course, group Q&A sessions, and instructor feedback.

Level: Beginner
Duration: 18 hours
Cost: Free to enroll, additional fees may apply
Outcome: Certificate of Completion

With four weeks of access to this course, students will learn who to use valuable tools like GitHub, R programming, and R-studio. You can study at your own pace using the courses quizzes, reading, and video lectures. After completing this course, you’ll have a firm handle on big data, experimental design, and R-markup.

During this course, you can complete assignments and receive instructor feedback to enhance your learning. According to Coursera, 29 percent of graduates from this course received a tangible career benefit, and 32 percent started a new career.

Best Data Science Resources

Best Data Science Resources

There are many data science resources available online to complement your learning. Look for tutorials, case studies, and discussions from data science resource publications. These online resources will all help you learn how different data science functions work. Below we’ve rounded up a few of the most useful data science resources.

Towards Data Science

Towards Data Science is a massive publication full of valuable resources. These resources include beginner-friendly tutorials such as how to learn Java, data science industry news, and summaries of influential projects. You will also have access to teachings on machine learning algorithm techniques and descriptions of personal data science pet projects.

Kaggle

From unraveling data sets to encouraging group discussions, Kaggle offers a dynamic range of data science resources. Users can access thousands of notebooks revealing how to implement data science techniques and algorithms. There are also courses available on Kaggle, and you can join multiple data science competitions.

Machine Learning Mastery

Machine Learning Mastery is a simple website for data science and machine learning resources. It has a vast collection of tutorials, e-Books, and information-packed articles. The theories and practices are concise and well broken down, and you can quickly find what you need through the filter and search features.

Why Learn Data Science?

Learning data science is a great career choice, as many well-paying jobs rely on data science skills. Data science graduates have the expertise to branch into many fields, including computer science, information technology, and tech.

It’s never been easier to learn data science. There are so many online data science courses and resources to enhance your studying. You can choose to take study for a few hours or a few months at a time, whichever works for you. With so much flexibility and opportunity in the field of data science, what are you waiting for?

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