Revolutionizing the very way we view information, data science has cascaded over several industries today, making it a necessity for their success and therefore, existence
INSOFE’s Data science
Our ability to amass, mine, and employ colossal amounts of data continues to transform every aspect of our lives. With applications within every major industry—including Banking, e-commerce, healthcare, transport, manufacturing and retail, to name a few—the skill-set required to create advanced techniques to utilize the power of data, and tell its story, is critical.
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INSOFE’s Data science curriculum teaches in-depth concepts pertaining to the Essentials of Engineering skills in Data Analytics, Deep Learning Applications, Foundations of Probability and Statistics, Artificial Intelligence, and Decision Sciences, offering extensive exposure to existing frameworks and algorithms to solve real-world problems and build products/services specific to their specialized engineering domain.
Well-equipped data scientists possess technical and practical skills that aid in identifying real-world problems right from their inception, their patterns, and the solutions needed to rectify them.
Predictive Analytics
Predictive analytics leverages various techniques such as data mining, machine learning, pattern identification, and artificial intelligence to analyze current data to predict the future. This historical data is inserted into a mathematical model that analyses key trends and patterns in the data. The model is subsequently applied to existing data to predict future occurrences.
Positive operational transformations in companies and business applications can be brought about through predictive analytics.
Analysts often utilize this process to decipher the probability of decisions leading to reducing risks, bettering operations, and increasing revenue.
Real-World Examples of Predictive Analytics
Predictive analysis has been used at an increased pace by a myriad of industries to attain competitive differentiation and upgrade every day business operations
In practice, predictive analytics can take on many different forms.
Identification of the possible abandonment of a service/product
A company that has employed a predictive analytics model can suggest incentives to customers that are likely to sustain their loyalty, based on historical data. Predictive analytics can be used in real-time to avoid customer agitation altogether.
Focusing marketing campaigns on selected groups
Predictive analytics and business intelligence can help anticipate customers that have the highest probability of investing in a product. This information can then be used on a specified group to optimize revenue.
Improve customer service through meticulous planning
Through the usage of advanced analytics and business intelligence, businesses can accurately predict demand. This ensures proper preparation and attainment of resources while avoiding wastage.
At INSOFE, the implications of progressive digital skills in today’s unremitting learning economy are wholly understood. By offering training and upskilling, INSOFE ensures that their students are equipped to be economically and educationally competitive in the real world by harnessing the power of Data Science and its concepts.
Prescriptive Analytics
This analytics concept is advanced, using past scenarios to comprehend the impact future decisions will have. A combination of business rules, constraints, desired outcomes, and historical data is used for prescriptive analytic optimization. This in-depth analysis showcases the following elements:
- Objectives
- Decisions
- Constraints
Seamlessly map the trail to success
Prescriptive analytic models are intended to gather data and operations to generate a roadmap that is effectively an indicative manual. Simulated actions are devised through artificial intelligence to specific scenarios to achieve success and avoid steps that lead to failure.
Understand real-time and long-term business operations
Both real-time and forecasted data can be viewed simultaneously to render decision-making that supports persistent growth and success. Contributing specific recommendations effectively streamlines decision-making.
Utilize your time better
Through the fast-paced turnaround of outcome prediction, decreased time is spent identifying problems and more time is invested in designing ideal solutions. Artificial intelligence can curate and process data comprehensively, effectively eradicating human error and bias.
INSOFE’S curriculum understands that Data Science holds a uniquely central position in growing industry needs and outfits each student with the indispensable skills to thrive in the real world.
Descriptive Analytics
Real-time and historical data are categorically scrutinized and utilized to extract insights on future outcomes. Data mining and aggregation are used to look into the past, so as to uncover the future.
Measures of Frequency
In descriptive analysis, it’s necessary to know the frequency at which a certain event or response is likely to transpire. It helps identify variables and new hypotheses, which can be further examined through experimental and inferential studies. As the data is extracted straight from the data properties, the margin for error is minuscule.
Providing an all-encompassing picture
When compared to other quantitative methods, descriptive analysis provides a broader picture of a situation. Several variables are utilised to conduct descriptive research.
A precursor to predictive analysis
While raw data is difficult to absorb and interpret, the metrics presented by descriptive analysis are increasingly focused. It can also be conducted as the precursor to predictive or diagnostic analysis, with insights into past occurrences that assure the success rate of present and future scenarios.
Learn these skills at INSOFE
As a Data scientist in the business sector, problem-solving capabilities and project management skills are pertinent.
Identifying strategic opportunities while developing communication abilities that ensure the information is successfully integrated into the business’s decision-making and production processes is of great importance.
At INSOFE, the curriculum not only contains big data and database skills necessary to handle data science projects at an enterprise scale but also provides students with the knowledge to solve real-world business problems. The curriculum understands growing industry needs and equips each student with the necessary skills to thrive.
From data acquisition and algorithm development to intellectual curiosity and business acumen: INSOFE’s Master of Data Science provides the training necessary for real-world applications, providing indispensable skills to achieve real-world success.
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