Data Science is extracting knowledge from structured or non-structured data by using different tools. It is a skill of 21st century to improve processes and gain insight of the information available. As compared to traditional Statistics, Data science not only finds value but also envisions future trends.
There are different components of Data Science, according to your interest you can be a part of this field. It is a blend of machine learning, business intelligence, statistics & programming languages. So you can choose either any one component to master in that particular area or you can do all the different parts to become a data scientist & can join the field. Following are few components of data science to give you the better understanding of data science.
- Fundamentals of Data Science– In this you will learn the basics of data science. It will include algebra functions & Business Intelligence. You will get to learn the interpret complex data by using different tools and can do the future predictions, which can be authentic decision support system.
- Statistics– This is a most important component of Data science. Statistics is a mathematic term used to perform technical analysis and interpretation of data. There is a theory of probability too on which statistics methods are dependant. In this you will learn the basic concepts of statistics i.e. features (mean, median, standard deviation, range variance), Distribution, Sampling, Bayes Theorem.
- Programming Languages– Understanding of programming languages is very important for a data scientist. It is not necessary to be expert in all the programming languages. Depending on your education background, expertise in any one programming language is would work. The most popular languages are R, Python and SQL.
- Machine Learning and Artificial Intelligence– One of the most common techniques for processing big data is machine learning. In this, good knowledge of supervised or unsupervised algorithms is required. Like Linear Regression, Logistic Regression, Random Forest, Decision Tree, Clustering etc. Ex, if you want to detect any fraud in digital finance company then machine learning tools are going to be used. There is computational algorithm built into the computer model which can find all the patterns of transactions and can find out the fault.
- Data visualization/Reporting – Good knowledge of visualization tools are very significant in Data Science. Ex. Google Charts, Tableau, Kibana etc. Data reporting means to collect & submit the data, which leads the analysis of the facts. It monitors the performance of different areas of the business.
- Big Data– Due to fear of missing out any important information it is very necessary to preserve the data, for that big data analytics is important. Name itself describe its meaning “big” or “huge”. Big data examine and analyze large amount of data and extract information for company growth and for comparison. Hospitality Industry, Healthcare sectors, retail businesses etc are some example of the sectors where big data analytics is used.
- Deep Learning– Deep learning is a function of Artificial Intelligence, which can work without human supervision to process the data. It can resolve and process huge amount of unstructured data easily, which a human brain would normally take decades to understand & process. It has solved the lot of limitations of traditional machine learning methods. In this one needs to understand the Neural Networks.
In simple terms, we can say data science is finding any useful and obvious insights from a raw data. It is used where your requirements are high & data is too big and complex. Data Science training will help you to find a better job opportunities. Now data science is not confined to just IT field but also useful in other leading industries. Data science experts are required in almost every field like entertainment, retail and service industry like hotels & tourism. You can start with basic and complete the course gradually. There are many certificates courses & advanced courses are available, which will increase your earning potential. With career growth you will also find the flexibility to work. Professional certification will help you to get jobs like business analyst, data engineer, research scientist or data architect etc.
If you are desire to do this course, then this is the right time to begin & jumps start your career.