There is an enormous increase in the distinctive data-related talent. With the increasing amount of data in the world, these is a huge need for data professionals in public organization, corporates and non-profits. There is a very limited talent for data-related analytics work, which is reflected by the ever-increasing salary packages offered to the Data Scientist.
McKinsey Global Institute reveals that “a shortage of the analytical and managerial talent necessary to make the most of Big Data is a significant and pressing challenge (for the U.S.).” Furthermore, the reports suggest that there would be substantial increase in the job opportunities for Data Scientist across the world.
Data Science is the Science of answering complex business questions with the help of data. Data Science is the combination of statistics, mathematics, programming, problem-solving, capturing data in ingenious ways, the ability to look at things differently, and the activity of cleansing, preparing, and aligning the data.
Data Science, generally answers several questions such as how a thing can be classified (Classification), Is this normal (Anomaly Detection), What’s next (Forecasting), How many things are required or how much is required (Regression), and How to group these things or criteria (clustering)
Regression algorithm helps in answering how many things are required or how much quantity is required. When there is a need to know the answer for how much or how many, it is wise to leverage and apply regression algorithm in the data. Regression Algorithm helps in making numerical predictions. Regression algorithm can be applied on the data using Apache Spark, SAS, R Programming, and Python.
Classification algorithm helps in answering if a data or element falls in which class. When there are only two classes, i.e., Class A and Class B, the algorithm is called Two-class Algorithm. Classification algorithm can also be applied even when there are N-Classes. When it is needed to classify a set of data into classes for decision making, classification algorithm comes into play. Classification Algorithm can be use. Classification algorithm can be applied on the data using Apache Spark, SAS, R Programming, and Python.
Clustering algorithm helps in grouping the set of data or a single entity in a cluster or a group. Basically, clustering algorithm answers the question how the data is categorized or organized. Clustering algorithm helps in organizing data in clusters for easier identification. When it is needed to find which set of data or entities fall under a specific cluster or group, clustering algorithm comes to play. Clustering algorithm can be applied on the data using Apache Spark, SAS, R Programming, and Python.
Data Science is the most sought-after factors in the present-day scenario. On the wake of increasing amount of data accumulated every day, one requires a sophisticated methodology – Data Science - to arrive sane results out of insanely humongous data. Data Science can be applied to data using any one of the tools available which includes R Programming.
SAS is one of the most widely used analytics tool for performing Data Analysis apart from R Programming and Python. SAS has huge capabilities and it can perform almost all the data warehousing functions, analytical functions, reporting functions and data science activities. At the outset, students will be taught the basic and advance SAS, after which Data Science algorithms will be taught to candidates.
Owing to increase in data accumulated and demand in analytics, Python is considered one of the best tools for performing Data Science activities other than SAS and R Python. Python like other languages has its own set of syntaxes, data types, operators, dates, functions and other components. We at Ampersand Academy, start from the basics of Python, and move on to the Python Analytics and then to Data Science.
We at Ampersand Academy, offer training on Data Science covering the algorithms mentioned above. These algorithms can be applied using various programming languages such as SAS, R Programming, and Python. However, it is mandatory to learn the Core / Base of SAS, R Programming, and Python before signing up for Data Science Program. We also offer clubbed program where we start from Basics of SAS, R Programming, and Python and move on to Data Science.
Candidates who are in pursuit of entering in to analytics can enroll with us for our comprehensive data science program which deep dives on four main data analytics tools. Furthermore, our data science curriculum can be custom made according to the requirement.