A few decades back the job role called data scientists didn’t exist. There were employees who used to analyze, organize, and clean the data. But they were no actual profession like data scientists. The modern-day data scientists possess exceptional skills which many firms are looking for.
Many organizations are also looking for the certified data scientist who will add more value to their growing business. Have an understanding of the following to boost your understanding of the skills to be a top data scientist
- Essentials of Data Science
- Probability and Statistics
- Programming
- Data Visualization
- Data Wrangling and Analysis
- Machine learning, deep learning, AI
- Communication Skills
Essentials of Data Science – The first and the most important skills one needs is knowledge about the essentials of data science, artificial intelligence, and machine learning. They should understand the topics that include:
- Details about machine learning and deep learning, and their differences
- Knowledge of common tools and terminologies
- The major differentiation between data engineering, business analytics, and data science
- Unsupervised Learning and Supervised Learning
- Regression Vs. Classification
Probability and Statistics – This is one of the main concepts that is required to generate high-quality models. Statistics is the process of analyzing the dataset to identify the unique mathematical characteristics. Machine Learning starts as statistics and then advances further. Mean, median, mode, variance, average, and standard deviation are used to describe the dataset. There are two major statistical methods: descriptive statistics and inferential statistics. After that come the different probability distributions, population, CLT, sample, kurtosis, and skewness. With advanced probability and statistics skills, one can easily integrate practices like Bayesian statistics to direct the probability of events based on past data and the possibility of recurrence.
Programming –One of the best skills ishaving sound knowledge of different data science programming languages such as C/C++, SQL, Python, Perl, and Java will be a great advantage. Among all these Python is the most preferred coding language needed in the job roles of data science. Among all these Python is the most preferred programming language needed in the job roles of data science. The programming knowledge helps the data scientists to well-organize the unstructured data sets. This will also help in transforming the data into getting accurate results. Python and R languages are the most preferred by many as they are quite easy to use. One can master their programming skills by taking up a data scientist certification. These are some programming languages that they will learn in the certification course:
- Python
- R
- Julia
- Java
- TensorFlow
Data Visualization – Data Visualization is the representation of the data in an easy-to-digest way, which includes charts, images, maps, and graphs. There are different kinds of areas where data scientists transform data so that they can visually view it. These visualizations are fonts, simple, lacking color, and various other aesthetical features. An expert in data visualization knows how to create a story out of the visualizations.
Data Wrangling and Analysis- Data wrangling or manipulation is the process in which getting the right data, combining relevant datasets, cleaning the data, and transforming it into a format that can be easily analyzed in the further steps take place. It basically transforms unstructured data into structured data. Data Analysis is an ongoing process in data science, in this process the transforming and scrubbing of data into a visual form takes place. This process focuses on answering specific questions of a dataset and validating the answer. Data Analysis is mainly done in Excel, SQL, and Pandas in Python. There are many certified data scientists who have mastered these skills by successfully applying them to enhance the profit margins as well as to improve the quality of the product.
Machine learning, deep learning, and AI- For a data scientist, having knowledge of machine learning, deep learning, and artificial intelligence are among the core skills. Machine learning is mainly used to build predictive models. The best way to learn machine learning is by practicing problem statements by doing a data scientist certification one can practice problems and enhance their skills.
Deep Learning is a high growth vertical in the stream of Artificial Intelligence. One can excel in this by mastering their skills in programming mostly in Python and must have good knowledge of mathematics and linear algebra. Knowledge of the following libraries is a must to have:
- PyTorch
- Keras
- TensorFlow
Communication Skills- Communication is the most important skill, the quality of an elite data scientist is to formulate the problem statement. One should properly communicate about the business perks of data, computational, and technology resources to the business executives. And also about other sectors of interest to the organization.While the number of skills that are needed to be among the elite data scientists is really long. But these skills will surely help you to stand out and to perform well in your career.
