The argument in favor of using filler text goes something like this: If you use real content in the Consulting Process, anytime you reach a review point you’ll end up reviewing and negotiating the content itself and not the design.Consultation
With an increasing number of companies waiting to capture and leverage Big Data insights, there is a skyrocketing demand for data scientists across all industry verticals. No wonder many students and IT professionals are now opting for data science training courses to make the most of this industry demand.
Even in terms of salary and growth opportunities, data science seems unbeatable! So, if you are also thinking of making a career in data science, it is best to know the top five things that companies look for while recruiting data scientists. Let's have a look.
Knowledge of programming languages
Although there is no need to be a master in coding, companies prefer candidates who have a fair knowledge of various programming languages. Right now, Python and R are the favourites among data scientists. However, you can also start with C or C++. The knowledge of programming languages proves handy while dealing with unstructured data sets,
Real-world problems into ML problems
While it is good to know how to handle machine learning (ML) problems, data scientists must have the ability to translate real-world problems into ML problems, which is quite challenging as real-world problems are ill-defined. Most importantly, they have to figure out a way to solve these ML problems.
Fair understanding of statistics
As machine learning demand statistics, data scientists are supposed to have a fair understanding of various statistical concepts such as mean, mode, standard deviation, probability distributions, hypothesis testing and much more! Knowledge in statistics proves invaluable in collecting, organizing, analyzing, interpreting, and presenting data to derive meaningful results.
Expertise in predictive modelling
Data scientists are experts in using data to predict and model various scenarios and outcomes. So, expertise in predictive modelling is considered a brownie point and is highly valued by recruiters.
Ability to visualize data
While working with big data sets, the ability to visualize data is a vital skill. A data scientist must know how to use data visualization to explain the generated data insights to others within a business. Many data scientists use various data visualization tools and create heat maps, line charts, bar charts, histograms, scatter plots, and more!
Apart from the above technical skills, companies also actively look for candidates possessing strong communication skills, business acumen, and critical thinking skills. So, if you are seriously aspiring to become a successful data scientist, it is high time that you join a Data Science Training Center. To have the best results, look for a training centre that has a proven track record of academic excellence and placement assistance.