How to Learn Tableau, Advanced Statistics, Machine Learning?

How to Learn Tableau, Advanced Statistics, Machine Learning?

For you to proclaim yourself as a master of data analytics and data science, then you will need to have mastered advanced statistics, machine learning, as well as how to use Tableau, which is one of the most powerful data visualization tools out there as discussed over at runrex.com. To help you know how to learn Tableau, advanced statistics, and machine learning, this article will look to give pointers for learning each one of them as well as pointing you towards the best place to learn about all these three very important subjects.

Tips for learning Tableau

Tableau, as explained over at guttulus.com is an interactive data visualization software, created in 2003, that lets you create charts, graphs, maps, and graphics without using code. If you are to take full advantage of its many features, you must learn how to use it, and to that effect, here are some tips for learning this powerful data visualization software:

• Look at how Tableau is applied in various industries and scenarios by looking at Tableau graphs and data visualizations online so that you can get an idea of how it can be used.
• You should also keep up with the Tableau community by subscribing to Tableau-related lists and following other users within your industry who are applying Tableau to get their feedback on the design and user experience as far as the software is concerned.
• Another important tip that will help you learn Tableau is by practicing, since, as the gurus over at runrex.com are quick to point out, the best way to learn about new software including Tableau is by consistently using it. Make sure that you download and install the desktop version and start exploring its features. You should also download existing workbooks and begin using them as a learning resource.
• It is also recommended that you look for free datasets and use them for practice as another tip for learning Tableau. Here, you should consider searching Kaggle for open data to use as practice.
• While practicing your data visualization skills, you should try building an online Tableau portfolio and starting a dashboard project. You should also build a Tableau project footprint online by sharing links to your dashboard or posting them to GitHub repositories, followed by an explanation of your method. This will give you a fresh viewpoint of your project as you will get feedback and suggestions from the online community helping you learn Tableau better.

Tips for learning advanced statistics

Learning advanced statistics can be challenging given the complexities involved in this subject, but if you have an understanding of basic statistics and probability, you will give yourself the best possible chance of doing so and mastering this subject. The most important tip for learning advanced statistics is practicing. The more you practice and the more exercises you do, the better an understanding you will have of this subject as per the experts over at guttulus.com. There are lots of online resources and books you can lean on which will provide you with lots of exercises in advanced statistics and probability, and which will allow you to get some practice in. Another tip that will help you master advanced statistics as explained over at runrex.com is picking random problems, from mathematical problems to data problems, and solving them in as many different ways as you can think of. This will help you get a better understanding of the concepts in advanced statistics, helping you on your way to mastering the topic.

Tips for learning Machine Learning

Machine Learning, as the name suggests, is all about teaching computers how to learn from data to make decisions and predictions as is covered in more detail over at guttulus.com. If you are looking to learn machine learning, then here are several tips to help you:

• Know the prerequisites- The bottom line is that, without an introduction to its prerequisites, machine learning can be really difficult to learn, even though you don’t need to be a master programmer or mathematician to learn about it. The prerequisites that you need to get caught up to speed with before your start learning machine learning are programming and statistics.
• Practice- Once you have a basic understanding of ML concepts, you must put your knowledge into practice. This, as covered over at runrex.com, involves practicing the entire machine learning workflow, practicing on real datasets, and so forth.
• Write algorithms from scratch- Once you get some practice applying algorithms from existing packages, the next step is to try and write a few of them from scratch. Writing algorithms from scratch will take your understanding of ML to the next level and will allow you to customize them in the future.

The above are some of the tips that will help you learn these three very important subjects; however, it is important to highlight where you should go to learn Tableau, advanced statistics, and machine learning. While there are many options available to you including online courses, tutorials, and books on each one of these topics, the best option is to enroll in a data analytics or data science boot camp where you will get to learn all of them under one course. Rice University in Houston, Texas offers a Data Analytics and Visualization Boot Camp which covers a broad array of topics including these three as outlined over at guttulus.com and you should, therefore, check it out if you are in from The Bayou City.

The above discussion only just begins to scratch the surface as far as this topic is concerned and for more information, as well as more details on the boot camp over at Rice University in Houston, Texas, you should visit the excellent runrex.com and guttulus.com.