Are there free online data analytics courses? Of course, there are! These courses are not just advantageous because they are free, or just because they are online and self-paced but guess what? They are top-notch!
Since data analytics is a crucial component of business, there is a rising demand for data analytics specialists. The evolution of technology and the everyday increase in data-dependent decisions has also been a case study.
All of a sudden, data analytics seems to be a hot topic, leaving you wondering what it is. You don’t need to look any further; World Scholars Hub has the best solutions!
Table of Contents
What is Data Analytics?
Data analytics is a general name for various types of data analysis. It deals with the use of available insights and trends to solve a particular problem. In simple terms, data analysis deals with analyzing data or statistics systematically.
Based on the understanding and application of the data patterns, data analytics is to the end that a scientifically effective decision is made. Scientifically in the sense that data has to undergo various steps and processes before a decision can be made.
Any type of information can be subjected to data analytics as it is the secret to performance optimization, profit maximization, and accurate decision-making in every business.
Another beautiful thing about data analytics is its job diversity. With data analytics, you can be a data analyst, business intelligence analyst, data scientist, data engineer, operational analyst, project manager, or IT systems analytics, to mention but a few.
There are various steps involved in data analytics, and all of these are for the growth of a business. Each of these stages holds a key to business efficiency.
What are the Steps Involved in Data Analytics?
Below are the 4 steps involved in data analytics:
1. Descriptive analytics:
Descriptive analytics deals with how well a business is going. The most frequently asked question at this stage is “What is happening in your business?”
In this aspect of data analytics, deep information is not needed. It answers the question of whether or not there is a smooth running of a business. Therefore, the answer is often not well-detailed.
2. Diagnostic analytics:
This is the step after descriptive analytics. Diagnostic analytics deals with the root cause of a problem. The question asked at this stage always starts with a why. For example: “Why is this happening to your business?”
With well-detailed information about the business, the “why” problem is put to light. This stage helps to identify business anomalies.
3. Predictive analytics:
This is the step after diagnostic analytics. In predictive analytics, previous statistics and algorithms are used to provide recommendations. The most frequently asked question at this stage is “what will most likely happen in the future?”
This technique is based on trends and patterns over the years. It is used to determine whether a particular trend will recur. It also helps to provide the best available recommendations for future happenings.
4. Prescriptive analytics:
This is the step after predictive analytics. Prescriptive analytics determines the best choice of action. This area helps to answer the question of “What should be done?”
It determines what to do and what not to do. This can be used to advise users on the possible results and what should be done for maximum business optimization. At this stage, even in the face of uncertainty, a data-driven decision is made.
What to Look For When Choosing A Free Online Data Analytics Course
Choosing the course most suitable for you is much more work than you think it is. Some factors must be considered before opting in for an online course.
Below are some factors to consider when choosing a free online data analytics course:
1. Credibility and rating:
This must be looked out for before choosing any course. This includes reviews given by students that have taken the course before. It determines how much a course can be trusted. You won’t want to opt-in for a course and along the line realize that it’s with a 1.0 rating. You wouldn’t like that, right?
2. Course duration:
Online courses could be short-term (a few hours to weeks) or long-term (months to years). The course duration should depend on your availability and level of comprehensiveness. Generally, long-term courses are often more detailed compared to short-term courses.
3. Intensity:
Online courses are a variety of beginners, intermediate, and advanced, while some are a series consisting of all of these stages. Other courses require you to have basic knowledge before opting in for the course.
When choosing a course in data analytics, choose a course most suitable for your current educational level.
4. Course accessibility:
Some free courses are accessible within a time range (temporarily accessible) while others are available for a lifetime. Choosing a course permanently accessible is the best because you can always refer back to them in case of uncertainty about a subject matter.
5. Supports and mentorship programs:
There are some withdrawals in most free courses and these withdrawals include course certificates, support, and mentorship programs. Some of these support and mentorship programs include discussion platforms, live lecture facilities, and simulation tools.
Despite this withdrawal, financial aid is an option in some of these courses.
6. Sharable certificate and financial aid:
The certificate issued after course completion serves as proof of professionalism. Although most online learning platforms require a token to obtain a shareable certificate while some platforms offer financial aid for students who want to study these courses for free and still be certified. Make sure you check whether financial aid is available if the certificates are not free.
What are the Best Free Online Data Analytics Courses?
Below are the best free online data analytics courses:
- Data Analytics Short Course
- Understanding Data Science
- Introduction to Data Analytics
- Introduction to Data analysis
- Math for Data Science
- Lean analytics workshop
- Introduction to data analysis using excel
- Bayesian statistics: from concept to data analysis
- Google data analytics
- Learn to code for data analysis.
10 Best Free Online Data Analytics Courses
1. Data Analytics Short Course
- Best for: Beginners
- Rating: 4.84 out of 5
- Duration: 15 minutes daily
- Platform: Career Foundry.
Data Analytics short course is a practical introduction to data analytics. In this course, you will start with cleaning and conclude with visualizations (including charts and graphs), and key insights. For better understanding, real data set will be used to address business issues.
This course contains an introduction to data, and also contains some exercises. Every day, you receive 5 daily lessons self-paced within the time range of 15 minutes.
Each tutorial contains a mixture of video introductions, written lessons, hands-on tasks, and interactive quizzes. It contains an introduction to data analytics which is a comprehensive study involving data cleaning, visualization, and final insights.
2. Understanding Data Science
- Best for: Beginners
- Rating: Not stated
- Duration: 2 hours
- Platform: Datacamp.
Understanding Data Science will broaden your knowledge of data science, machine language, data visualization, data engineering, and cloud computing. This course comprises 15 videos and 48 exercises.
In this course, you will learn the basics of data science, data collection, storage, preparation, exploration, visualization, experimentation, and prediction.
You will also learn data interpretation and incorporation into daily life. Also, you will be taught the roles of a data scientist without having to worry about coding.
3. Introduction To Data Analytics
- Best for: Beginners
- Rating: 4.8 out of 5
- Duration: 6 months
- Platform: Coursera.
Introduction to Data analytics will take you through data analytics from scratch as no prior experience is required. This course will enlighten you on the in-demand skills needed to get you ready for a career in data analytics.
In this course, you will learn how to prepare, organize, analyze and visualize data for analysis. Also, you will be taught how to use spreadsheets, SQL, and R programming to complete analyses and calculations.
4. Introduction to data analysis
- Best for: Beginners
- Rating: Not stated
- Duration: approximately 6 weeks
- Platform: Udacity.
Introduction to data analysis contains information on how to make queries, organize your data into a usable format, and address any issues. It also contains lessons on examining data, looking for patterns in it, developing your data intuition, and making judgments, conclusions, or predictions.
You will also be thought the best ways to express your findings. Additionally, you’ll learn coding in a more concise and faster way using the Python libraries NumPy, Pandas, and Matplotlib.
As a prerequisite to this course, you should be comfortable with programming in Python and knowledgeable about its concepts, before enrolling in this course. If not, they have a course on “introduction to python programming course” that will take you through these.
5. Math for Data Science
- Best for: Beginners
- Rating: Not stated
- Duration: 5-6 hours.
- Platform: Alison.
Math for Data Science covers the fundamentals of probability, statistics, and linear algebra as they relate to using math in data science. As a basic understanding of math is required of every data professional (data scientist, data analyst, business analyst, or data engineer), this course covers every of the required aspects.
This course is unlike every abstract, unapplied math. At Alison, you will learn math that will enable you to influence the world. This course is the third course in a series. To get the best out of this course, it is advisable to take these first two courses on data science before taking maths for data science.
6. Lean Analytics Workshop
- Best for: Beginners
- Rating: 4.6 out of 5
- Duration: 2hrs 23 minutes
- Platform: Udemy.
Learn analytics workshop helps you to understand the fundamentals of analytics, the data-driven mindset, and lean startup principles. In this course, you would look at six examples of how business models relate to start-ups of all sizes.
You will also learn how to know the time to move forward with a decision and apply the concepts of Lean Analytics to established businesses and products.
7. Introduction To Data Analysis Using Excel
- Best for: Beginners
- Rating: Not stated
- Duration: 4 weeks (at 2-4hrs per week)
- Platform: edX.
Microsoft Excel and its integrated pivot tables are one of the best analytical features for data analysis. In this course, you will learn how to perform data analysis using Excel’s most well-liked features.
In Introduction to data analysis using excel, you will discover how to make pivot tables in Excel using a range of rows and columns. You will also witness the effectiveness of Excel pivots in action, including its capacity to summarize data in a variety of ways, facilitate quick data exploration, and generate insightful knowledge from data gathered.
8. Bayesian Statistics: From Concept To Data Analysis
- Best for: Intermediate
- Rating: 4.6 out of 5
- Duration: 12 hours
- Platform: Coursera.
The Bayesian approach to statistics will be introduced in this course through the study of probability and data analysis. Also, the foundations of the Bayesian approach as well as its application to typical data types will be taught.
The Bayesian approach will be contrasted with the Frequentist approach as well as the advantages of the Bayesian approach. To create an engaging learning environment, this course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards.
9. Google Data Analytics
- Best for: beginners
- Rating: 4.8 out of 5
- Duration: 6 months (at 10 hours per week)
- Platform: Coursera.
Google data analytics gives you a thorough understanding of the procedures and methods a junior or associate data analyst employs daily.
In this course, you will also learn important analysis methods which include data cleaning, analysis, and visualization using these tools: spreadsheets, SQL, R programming, and Tableau. You will also learn how to display data findings on dashboards, presentations, and popular visualization platforms.
10. Learn To Code For Data Analysis
- Best for: beginners
- Rating: 3.5 out of 5
- Duration: 24 hours
- Platform: OpenLearn.
Learn to code for data analysis will teach you how to create your computer programs with coding (one line of code at a time). Due to the popularity of python across all academic fields, it is the programming language used in this course.
Using real data from the World Bank, the World Health Organization, and other organizations, coding exercises and write-up analyses using the well-known Jupyter Notebooks platform will be conducted. This is to enable you to instantly see the outcome of running your code and makes it easier for you to spot and correct errors.
In this course, you will learn how to access open data, prepare it for analysis, create visualizations, and document and disseminate analyses publicly and privately.
Frequently Asked Questions On Free Online Data Analytics Courses
What is the best free online data analytics course?
Data Analytics short course by CareerFoundry
Is data science the same as data analytics?
No.
What are the job opportunities available for me if I study data analytics?
With data analytics, you can be a data analyst, business intelligence analysts, data scientist, data engineer, operational analyst, project manager, IT systems analytics and lots more.
Are all data analytics courses suitable for beginners?
No, some courses require some prerequisite knowledge in some fields before you can opt-in for the course.
How important is data analytics to a businesss?
Data analytics is the secret to performance optimization, profit maximization and accurate decision making in every business.
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Conclusion:
Suddenly everyone seems to be talking about data analytics and you be like “What is this data analytics like?” As promised earlier, we hope you’ve been able to understand what data analytics is all about.
We also hope you’ve been able to choose from a variety of free data analytics courses. We will like to hear from you!
