Best Recommendations for Data Science Courses Online That Can Make You A Reliable Data Scientist Who Is Demanded By Many Industries

15 Best Recommendations for Data Science Courses Online That Can Make You A Reliable Data Scientist Who Is Demanded By Many Industries

If you now often hear about data science, but actually this term has been around for a long time. John Tukey described one of them in 1962 where he once described a field he called “data analysis, “ which can be analogous to modern data science when viewed today.

And over time, data science has become a very important tool used by companies to determine their strategic steps.

The current situation in which companies are doing a lot of data-driven business development makes the need for people who understand and master data science continues to increase. And it turns out that a proven way to improve one’s competence in processing big data is to take the best data science courses online from trusted course providers.

The company sees that data science is one of the keys to the success of a business. With data science, companies can get new insights from existing data, which are then collected and compiled.

The application of data science can vary according to the technology and techniques used. And as time goes on, feature-rich end-to-end platforms continue to be developed and are often used for data science and machine learning.

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Why data science is important?

We must have agreed that data science is now important.

But to know why data science is important and how data science plays a role in many things, we also have to understand first what data science is.

According to Wikipedia, data science is an interdisciplinary field that focuses on extracting knowledge from data sets (and these are usually large and are often referred to as “big data”). The results are then applied to determine the steps in solving problems of many application domains.

Data science can include many things such as preparing data for analysis, identifying data science problems, analyzing data, developing data-driven solutions, and informing and presenting findings to high-level decision-makers.

In practice, data science can involve many branches of science such as computer science, statistics, information science, mathematics, information visualization, data integration, graphic design, complex systems, communication, and business.

One person who has successfully practiced it is Nathan Yu (a statistician and data visualization expert). At software and design consulting firm, he connects data science with human-computer interaction with the aim of allowing users to intuitively control and explore data.

The many successful examples then make many industries, especially those involving big data, start to continue to use data science to obtain data, identify problems, and formulate data-based solutions. This condition is further strengthened by a statement from the American Statistical Association in 2015 which states that database management, statistics, and machine learning, distributed and parallel systems are the basic professional communities.

Is data science the same as statistics?

Some statisticians think that data science is the same as statistics, but some think otherwise.

One statistician who agrees is Nate Silver. According to him, data science is not a new science, rather it is another name for statistics.

On the other hand, some statisticians think that data science is not statistics. And even they think that the two things are different. According to them, data science is more focused on problems and techniques for digital data. Who are they? Here are some of them:

  • Vasant Dhar. According to him, statistics are more focused on quantitative data and descriptions. While data science focuses more on quantitative and qualitative data (eg images) and also places more emphasis on prediction and action.
  • A data scientist named Vincent Granville and Andrew Gelman a professor of statistics and politics from Columbia University considers that statistics are unimportant from data science.
  • David Donoho, a scientist from the United States and also a professor of statistics at Stanford University. He wrote that data science is not distinguished from statistics by the size of the datasets or the use of computers. And according to him, many graduate programs are wrong in advertising because they mention their analytical and statistical training as the core of a data science program. According to him, data science is an applied science that grew out of traditional statistics.

What are data science courses?

Data science courses are courses available specifically to study data science and other related matters. And the good news is that it is now possible for you to take online data science courses.

With data science, we can bring together statistics, data analysis, informatics, and other related methods to analyze and understand events with data.

Data science uses theories and techniques adapted from various fields related to mathematics, statistics, information science, and computer science.

But you need to know that data science is different from computer science and information science.

The need for data scientists continues to grow. Someone who wants to increase their competence in the field of data science can consider taking an online course about it.

Are the data sciences courses important?

With our entry now in the era of information technology, the current era has changed, especially those related to science.

Information technology has an impact on the information explosion. It has become commonplace that now you can find a lot of data, even many of which turn out to be big data.

It takes science to handle the data explosion. Science is expected to be able to organize these data, analyze them, process them, from ordinary data to become more meaningful data. This is where data science comes to be the solution to the data explosion which is a consequence of the information technology era.

Yes, data science courses are important. In fact, industries and businesses are now in dire need of data science to help companies carry out data-driven development. So surely it will take more people who are reliable in the field of data science.

Can we learn data science on our own?

Before answering this question, of course, what must first be ascertained is what part of data science you want to study.

If you want to learn basic things like what data science is and how to apply data science, of course, you can find the answer yourself online. You can easily search for literacy-related to it through the Google search engine, search for videos on Youtube, or listen to explanations about data science through podcasts.

However, if you want to learn more about data science, it is highly recommended that you have an expert mentor who is ready to accompany you while you study it.

As explained above, data science encompasses many other disciplines. Of course, there are also a lot of data science practices, depending on where you want to master it.

So if you are someone who asks if you can learn data science yourself, then the answer is yes you can, but to get good learning outcomes, you must be accompanied by experts who have proven good in the field of data science.

Best-recommended data science courses online.

What online courses should you take for data science?

In this section, what we would like to recommend are courses that are close to the application of data science. It’s not about courses that just explain what data science is all about.

If you read this article from the beginning, of course now you can understand that in practice, data science is related to statistics, analysis, business, and even programming languages to process datasets.

These recommended online data science courses are perfect for those of you who want to learn about them in-depth with examples of real-world projects on the application of data science.

In the list of courses here, you will also be able to see the skill level and duration of completion of each course, so that you can decide for yourself which data science online courses will suit you.

The following is a list of best-recommended data science courses online:

1. Udacity Data Engineer online course.

If we talk about big data, of course, data engineering is the foundation.

By taking this Udacity Data Engineer online course you will learn how to build a production-ready data infrastructure which will be an important skill to advance your data career.

Skills to be learned: Data Modeling, Data Pipelines, Data Lakes, Spark, Airflow.

Skill level: intermediate, with an estimated completion time of 5 months.

To take this online course, it is expected that you have a correct understanding of intermediate Python and SQL.

2. Udacity Data Scientist online course.

Of course, to carry out proper data science in an industry, a reliable data scientist will be needed. This online course will guide you to become one of them.

With the Udacity Data Scientist online course, you will learn how to build effective machine learning models, run data pipelines, build recommendation systems, deploy solutions to the cloud with industry-appropriate projects.

Skills to be learned: Machine Learning, Deep Learning, Software Engineering.

Skill level: advanced, with an estimated completion time of 4 months.

There are no special prerequisites to take this online course.

3. Udacity Programming for Data Science with Python online course.

Python is one of the most popular programming languages because Python has the logic as humans think.

Udacity Programming for Data Science with Python online course is one of the best Python for data science courses online. With this course, you’ll learn the essentials of programming tools for data professionals like Python, SQL, the Terminal, and Git.

Skills to be learned: Python, Numpy & Pandas, SQL, Git, and GitHub.

Skill level: beginner, with an estimated completion time of 3 months.

There are no special prerequisites to take this online course.

4. Udacity Business Analytics online course.

To get certain insights from big data, what needs to be done is the ability to collect and analyze data.

This is where business analytics comes into play.

With the Udacity Business Analytics online course, you will gain basic data skills that can be applied to all industries. Here later you will learn how to collect and analyze data, create business model scenarios, and communicate your findings with SQL, Excel, and Tableau.

Skills to be learned: Excel & Spreadsheet, SQL, Data Visualization, Data Dashboards.

Skill level: beginner, with an estimated completion time of 3 months.

There are no special prerequisites to take this online course.

5. Udacity Data Analyst online course.

If you have seen above that there is an online course to become a data scientist, in this course, you will be guided to become a reliable data analyst.

Surely this data analyst will become a professional who will later play a very important role in the field of data science.

With the Udacity Data Analyst online course, you’ll learn how to use Python, SQL, use statistics to derive hidden insights, communicate critical findings, and create data-driven solutions.

Skills to be learned: Data Wrangling, Matplotlib, Bootstrapping, Pandas & NumPy, and Statistics.

Skill level: intermediate, with an estimated completion time of 4 months.

To get better results, it is recommended to have a good understanding of SQL and Python.

6. Udacity SQL online course.

SQL is the main programming language for big data analysis.

With the Udacity SQL online course, you will learn to be more proficient in SQL as well as learn to make decisions based on insights and be able to make good business strategies.

Skills to be learned: SQL, PostgreSQL, JOINs, Subqueries, Window Functions, Partitions, Data Cleaning, DDL, DML, Relational and Non-Relational Databases.

Skill level: beginner, with an estimated completion time of 2 months.

To get better results, it is recommended to have a basic understanding of data types.

7. Udacity Data Analysis and Visualization with Power BI online course.

Online courses with this learning topic are new and not many course providers offer them.

With the Udacity Data Analysis and Visualization with Power BI online course, you will learn to master the skills needed to become a successful data analyst such as processing initial data, visualization, performing analysis using Power BI as the main tool.

Skills to be learned: Power BI, Data Visualizations, Data Modeling, Extract-Transform-Load, Data Analytics Expressions.

Skill level: beginner, with an estimated completion time of 3 months.

To get better results, it is recommended to master Microsoft Excel.

8. Udacity Data Streaming online course.

Data streaming is a continuation of the application of advanced data science.

With the Udacity Data Streaming online course, you’ll learn how to stream data to unlock important insights in real-time.

Skills to be learned: Data Streaming, Spark, Kafka, Kafka Streaming, Spark Streaming.

Skill level: advanced, with an estimated completion time of 2 months.

To get better results, it is recommended to have a good understanding of intermediate Python, SQL, and have experience with ETL.

9. Udacity Data Product Manager online course.

This online course is one example of how data science can be applied to a business.

With the Udacity Data Product Manager online course, you will hone your skills in the field of Data Product Management by learning how to apply data science to build products based on data, in this case: a scalable data strategy, to provide a good experience for the right users, and at the right time.

Skills to be learned: Data Science, Product Management, Product Design, Data Visualization, User Journey Maps.

Skill level: intermediate, with an estimated completion time of 3 months.

To get better results, it is recommended to have a good experience in the field of Prior Data Analysis and Product Management.

10. Udacity Data Architect online course.

Organizing and planning the flow of data is very important in data science.

With the Udacity Data Architect online course, you will learn how to plan, design, and implement enterprise data infrastructure solutions, as well as create blueprints for your organization’s data success.

Skills to be learned: Entity Relationship Diagrams, Relational Data Design, Online Analytical Processing, Operational Data Stores, Data Lake Architecture, and Data Governance.

Skill level: advanced, with an estimated completion time of 4 months.

To get better results, it is recommended to have a good understanding of intermediate Python, SQL, and basic ETL/Data Pipelines.

11. Udacity Predictive Analytics For Business online course.

Data sets turned out to be the main basis for making predictions in a business.

With the Udacity Predictive Analytics For Business online course, you’ll practice how to define patterns to predict upcoming trends and outcomes. With good analytical skills, you will be able to provide high-value solutions to various business-critical problems.

Skills to be learned: Data Wrangling, Classification, A/B Testing, FOrecasting, and Segmentation.

Skill level: beginner, with an estimated completion time of 160 hours.

To get better results, it is recommended to master Algebra, Descriptive Statistics, and Excel earlier.

12. Udacity Data Visualization online course.

To communicate data that has been processed so that it can be read comfortably, surely it will take the ability to visualize the data.

With the Udacity Data Visualization online course, you will learn how to combine data, create data visualizations, and create narratives to tell impactful stories behind the data presented, and make strategic decisions based on data.

Skills to be learned: Data Visualization, Tableau, Dashboards, Data Storytelling.

Skill level: beginner, with an estimated completion time of 4 months.

To get better results, it is recommended to have a good understanding of Basic Data Analysis.

13. Udacity Programming for Data Science with R online course.

R is one of the popular programming languages for data science besides SQL.

With the Udacity Programming for Data Science with R online course, you will learn the basics of data programming tools such as R, SQL, command line, and Git. With you having a good mastery of these programming tools, your career in data science will be even better.

Skills to be learned: R, SQL, Git.

Skill level: beginner, with an estimated completion time of 3 months.

There are no special prerequisites for taking this online course.

14. Udacity Data Science for Business Leaders online course.

A business leader will certainly need a good mastery of data science to determine the strategic steps of his business.

With the Udacity Data Science for Business Leaders online course, you’ll learn how to leverage the power of data science in your business by mastering the platforms, processes, and people involved.

Skills to be learned: Business Strategy, Data Science, Data Architecture, Machine Learning, Human Capital.

Skill level: intermediate, with an estimated completion time of 2 months.

To get better results, it is recommended to have a good understanding of statistics, probability, and also have experience in the business.

15. Udacity Monetization Strategy online course.

Although product monetization strategy is part of product management, it turns out that here a Growth Product Manager uses data science to determine the strategies they will take.

With the Udacity Monetization Strategy online course, you will be honed in your ability to be more observant in determining product monetization strategies based on data. The right product monetization decision will make the company’s profits even better.

Skills to be learned: Product Management, Monetization Models, Pricing Strategy, Buyer Personas, Lifetime Value, Customer Acquisition Cost, Pricing Metrics, Growth Strategy.

Skill level: intermediate, with an estimated completion time of a month.

To get better results, it is recommended to have a good experience in prior product management.

Conclusion.

With us in the era of information technology, the consequence that then exists is the emergence of a data explosion.

Data will only become data if it is not collected, analyzed, and processed.

However, if these data are analyzed and processed, they will provide many useful insights for our industry.

Data science is a knowledge for processing big data.

Data science itself includes many other branches of science, but still has the same goal of providing new insights that may not have been seen until now.

In this article, we do not provide information about the data science understanding course. However, here we provide more information for data science online courses which are more for their application in the field.

We see that learning data science should not be arbitrary. Therefore, you must learn from experts who are experienced in this field.

We took the online data science courses above from Udacity as one of the trusted course providers, which has advantages that will benefit people who enroll in their courses.

Some of the advantages of the Udacity Nanodegree program are:

  • Udacity’s commitment to providing expert and experienced mentors in their fields. People who join courses at Udacity will get intensive assistance, and they can freely contact their mentors and ask anything they don’t understand.
  • All Udacity courses have real-world projects that people who have enrolled in the course can participate in. This section is very beneficial for the students because they can at the same time know how to practice data science in the field.
  • Udacity provides online courses where registered people can determine their own study schedule. Udacity realizes that everyone is busy and has a different pace of learning.
  • Udacity also has a career service for people who have joined. Although this service is not a guarantee of getting a job, it can be very helpful in preparing someone for a better career.

If you want to study in a free online course on basic understanding of data science, Udacity also offers free courses covering topics such as Intro to Data Science, Intro to Data Analysis, SQL for Data Analysis, Database Systems Concepts & Design, Intro to Inferential Statistics, Spark, and Data Analysis & Visualization. You can get these data science online courses for free here.

So, are you interested in being able to apply data science in an industry?

Make sure you take the data science online courses above. Tailor it to your interests and you will gain important skills in data science that can be applied in all industries.


References:
Wikipedia: Data Science.

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