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Data analysis is being used more today than ever in our entire history. Every company, be it small or big, must implement data analysis to stay relevant in a rapidly changing environment. Failing to do so could be disastrous for any company. Therefore companies are investing heavily in data analytics teams to stay in business for the foreseeable future. This is why Data analytics courses have soared in popularity amongst mid-career professionals, working either in the data analysis or management teams. It is a tremendous skill-up opportunity for them and could open up doors for promotion or better opportunities elsewhere.
What is data analytics?
Data analytics is a generalized term describing the entire process of analyzing data and finding insights. The discipline of data sciences consists of
- Mathematics
Statistics, linear algebra, probability theory, calculus, linear regression, and Bayes’ theorem.
- Data visualization.
Data visualization software, such as tableau, wrapper, Sisense, Plotly, Qlik, and even excel.
- AI technologies
- Machine learning
Machine learning is an integral part of data science. It is used for developing algorithms that can learn through analyzing data sets to find patterns and make decisions with little human intervention.
- Deep learning
Deep learning is an advanced version of machine learning. It can find patterns and make decisions on its own. Data analysts only need to feed raw data and set up general parameters.
- Cloud Computing
A key aspect of better data analysis is the availability of higher computational powers. Being able to constantly increase the size of datasets is very crucial for staying relevant. For smaller ventures, it is not feasible to maintain sophisticated servers and computers. Therefore outsourcing it to a cloud computing service provider is the only choice left.
For practical purposes, a mid-career professional does not need to learn all the subjects mentioned earlier in greater detail. They just need to know the practical aspects of the data science discipline.
Why are online data science courses better for working professionals?
Working professionals don’t have the opportunity to attend regular data analytics courses. They can only participate in a regular course by taking unpaid leaves or leaving the job altogether. Online data science courses are directed explicitly toward working professionals. Most institutions provide two types of courses. One is a mix of online and offline classes. The classes are held on weekends, allowing the professionals to maintain their work-life balance. The other is a complete online course for people who do not want to or don’t have time to attend offline classes.
What to expect from the best online data analytics courses?
- Basics of data science.
For people who are entirely new to the subject, having classes dedicated to understanding the basic concepts and clearing any doubts is of utmost priority. Most institutes will only sell the course in video format. But this could be problematic for beginners, who will need someone to help them with the process. The best online data analytics courses will hold online classes and also provide the course in video format.
- Data visualization
A data analyst’s most significant responsibility is creating dashboards that will help visualize the insights. Data analytics courses will cover data visualization techniques using various software. Most courses will include classes on two data visualization software, excel, and tableau.
- Programming language
Having basic programming skills is of utmost priority for data analysts. Most institutes choose python over other programming languages because of the availability of free resources and libraries.
- Machine learning and deep learning for practical use
Data analysts will have to use machine learning & deep learning during predictive and prescriptive analysis. Therefore, the best online data analytics courses will include machine learning and deep learning classes. It will also focus more on the practical use of machine learning and deep learning depending on the requirements of modern businesses.
In predictive analysis, the goal of the data analyst is to find the future projection of a company’s performance and make them aware of the lurking dangers. The accuracy of such a prediction depends on the size of the data set. Also, to what extent the data analysis teams managed to clean it out of any irregularities?
In prescriptive analysis, the goal is to set up an algorithm using deep learning that can give actionable insights to the company. It is the most complicated form of data analysis and requires enormous data sets.
- Cloud Computing training
The best online data analytics courses will teach in & out of the cloud computation process and familiarize the students with various cloud computing service providers.