Data Analyst Courses:- For the students aspiring to become data analysts or risk management analysts in insurance fields, an actuary course is a good option. The reason for the same being, they will get to learn the basics of mathematical as well as probability equations. It is this knowledge that is required in collecting data and carrying out risk management for the insurance claims.
Well, there are a number of data analyst courses these days. So the students get many options to choose the most suitable one. Following are some of these:
PGDBA is a two years course, that provides the students with a great experience of multifaceted learning. It includes training in technological, statistical as well as business aspects of analytics. During different semesters, students get to know about probability processes, statistical structures in data and statistical inference. The course also includes machine learning and algorithm design.
This course, one of the data analyst courses, puts focus on the tools like Python, SAS, R, SQL, Spark, Hadoop and some more. It also focusses on skills of modeling and analytics, along with communication and visualization skills. The course is helpful in the application of analytics in business-related issues related to marketing, retail, financing and some more.
Also called PGP-DSE, the course, like the other data analyst courses, helps create professionals who want to succeed in the digital economy. This course offers programs in critical competencies like data science, analytics, machine learning, cloud computing and more. It’s an intensive as well as an extensive course. It works while blending two aspects – theory and applications.
This one’s a unique course as it covers almost the entire world of business applications. Hence it’s a bit different from the common data analyst courses. It supports the engineers as they are prepared to face the great advancements in the industry all around at such a fast pace. It also takes into consideration data science, big data engineering and analytics.
The tools covered in this data analyst course are R, Spark, Python, marketing analytics and others. This course requires three semesters and is a combination of personalized learning as well as collaborative approach.
It covers the complete data life cycle through R and Python. Python includes data mining, text analytics, machine learning, predictive analytics, data visualization, and deep learning.
It is a two years’ data analyst course that is more than half about business related knowledge while the rest is about analytics. The course covers data mining, advanced statistics, optimization techniques, SQL, predictive analytics, cognitive technologies, Fintech, IOT, and machine learning algorithms. The analytical tools are the best software and open source software Python.
This one is for students who want to be a part of the data analysis world through online education. It covers about ten data analyst courses. It covers cluster analysis, statistical programming in R, practical applications of machine learning and natural language processing. Students are required to come up with data products that can solve real-world problems.
Provided by Microsoft, this course expects some knowledge in the students about R or Python. These two are the most popular languages currently for data science programming. This course includes subjects like data exploration, probability, and statistics, an introduction to machine learning and visualization.
A number of online data analyst courses are available here, that too for free. Topics covered are methodology, data science 101, programming in R, open source tools and hands-on applications. The course is more time taking for the beginners.
The online course mainly focusses on machine learning. It teaches the students how the computers ‘learn’ and also teaches them mathematics while going some deep into it. For this course, the students are expected to have some knowledge of matrices and calculus.
Demand for data analysts with great skills is on a high and is expected to grow with time. With the increasing need, new technologies are coming into the picture for different businesses.