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Scaler Academy, Redefining Data Science & Machine Learning

The 11-month program by Scaler Academy is curated by Data Scientists from top tech companies and experts from McKinsey and Bain.

Data Science is currently one of the most sought after disciplines in the tech world. According to the National Association of Software and Services Companies (Nasscom), the Data Science sector in India is estimated to grow eightfold and be worth over 16 billion dollars by 2025. Being one of the most sought after jobs, organisations are constantly on the lookout for quality DS employees both for Business and Product roles. Currently, recruiters see a disparity between Demand and Supply roles. To address this concern and ensure learning with strong quality output, Scaler Academy has introduced – Scaler Data Science & ML course to allow every learner to have an in-depth and hands-on learning experience.

What Is Data Science, And Why Is It Important?

Data Science uses large amounts of data to answer various questions in a more efficient and precise manner. Data Science allows us to understand what happens, why it happens, what will happen in the future, and how to manipulate this data to personalise results. Data Science and its study are pivotal for technology progress, from making apps more consumer-friendly to helping tech companies with business strategies to extrapolate far more accurate results. 

Where Is Data Science Used?

Data Science and Machine Learning have diverse applications within the industry. It can not just be used in the tech industry but also for marketing, psychology, human resources, economics, biomedical science, and many more. The most common application of Data Science and Machine Learning is in product recommendation systems.

Product recommendation systems are used in both product and service-based companies for various applications. It is most commonly used in the e-commerce industry to personalise the shopping experience for customers. Data Science is used to extract data from the behaviour of the customers to construct a strategy. Information is collected from social networks and search results along with data on browsing history, purchases, tastes and preferences, and sociodemographic information of the public of interest. Using this information, a consumer can experience the convenience of having the shopping experience curated to one’s preferences without putting in the work. It also helps the product company push their products to prospective buyers strategically.

What is different about the Scaler Data Science & ML program?

Scaler offers a comprehensive curriculum to hone professionals for the following job roles,

  1. Data Scientist, ML Engineer
  2. Data Engineer, ML Ops Engineer
  3. Data Analyst, Business Analyst, Product Analyst

The 11-month program is curated by Data Scientists from top tech companies and experts from McKinsey and Bain who have helped design a curriculum to teach product and strategy. Scaler Data Science & ML learners start the course by building a solid foundation in Data Structures and Algorithms. The students then learn Mathematics, followed by Data Mining, Statistical Analysis, Data Science, Machine Learning, Deep Learning and Big Data. More than 45 critical tech tools will also be taught.

Students get practical hands-on experience by handling real-life Data Science & Machine Learning business problems. The business cases span multiple industries such as logistics, biotech, entertainment, health, finance, and e-commerce. These projects are built in partnership with Scaler’s partner companies to enable learners to work on actual problem statements and tackle messy or complicated datasets.

Scaler Academy has also been organising weekly MasterClass where experienced instructors from the industry talk about the applications of Data Science and Machine Learning in different disciplines. This has encouraged students to listen and understand the depths of what it takes to work in the field. With Scaler’s course structure, mentorship program, interview preparations and placements, it is one of the most promising choices for students and professionals who plan to start a career in Data Science and Machine Learning.