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Over 80% of Data Scientists struggle with real-world datasets despite training: Scaler

Scaler Academy, a leading ed-tech start-up for upskilling students and working professionals, today announced their new program for engineers looking to get specialized in Data Science and Machine Learning. The course is called Scaler Data Science & ML. It has been developed based on insights from a survey conducted by Scaler with over 100 data scientists working with the top 50 tech and product companies globally.

According to the survey conducted by Scaler Academy:

More than 95% of respondents highlighted the need for Data Scientists to solve open-ended business problems. However, most other courses available offline & online tend to focus only on teaching how to optimize the accuracy of algorithms rather than how to impact the business positively.

Over 80% of respondents shared that they struggled initially because the datasets that a data scientist works within the real world are massive and fragmented, non-standard, messy, and sometimes incomplete.

50% of respondents admitted that they struggle to understand research papers. Data Science, Machine Learning, and Deep Learning are rapidly evolving fields, and new research reports are being published constantly.

To address these demands from software professionals, Scaler Academy has curated the Scaler Data Science & ML course to allow every learner to have an in-depth and hands-on learning experience. Experts from McKinsey and Bain have helped in designing a curriculum to teach product and strategy. The business curriculum is integrated seamlessly into all projects. Students will get practical experience in identifying Data Science & Machine Learning problems in real-life business problems. The business cases will span multiple industries such as logistics, biotech, entertainment, health, finance, and e-commerce. These projects will be built in association with Scaler’s partner companies to enable learners to work on actual problem statements and tackle messy or complicated datasets.

Scaler Data Science & ML learners will also learn how to read and absorb research papers. Scaler will also aid learners in case they want to write and publish research reports of their own.

Software engineers with a minimum of 1 year of experience will be eligible to enroll for the Scaler Data Science & ML program. The course will start by building a strong foundation in Data Structures and Algorithms. Then learners will dive into 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 during the length of the course. The most impactful ones being TensorFlow, PyTorch, Kafka, PySpark, Airflow, and AWS. The program will run for 11 months and will prepare aspiring engineers for roles in 3 broad buckets: (1) Data Scientist, ML Engineer; (2) Data Engineer, ML Ops Engineer and (3) Data Analyst, Business Analyst, Product Analyst

Speaking on the launch of the new program, Abhimanyu Saxena, Co-Founder, InterviewBit & Scaler Academy, said, “Data Scientists and Machine Learning experts enable companies to make better decisions. They provide a guiding light to the entire organization, spanning departments as varied as Strategy, Product, Design, Engineering, HR, Finance, Marketing, and Recruiting. They are the unsung heroes who have been guiding their ships through turbulent storms. There is a lot of interest in the industry to work with appropriate people for this critical role. Leading tech companies are willing to pay an average of INR 24 Lakhs per annum to good quality data scientists & ML experts. Still, almost all organizations are struggling to hire the right talent due to the current scarcity. With the help of Scaler Data Science & ML, we aim to bridge this gap.”

“We have run the course by leaders across multiple companies, and they have validated our research findings and the curriculum. All of them and our existing partner companies that have already hired 2000+ Scaler Academy learners have expressed sincere eagerness to hire talent produced through this program. We strongly believe our program will enable engineers to build a sustainable and successful career in the Data Science and Machine Learning space.” he added.

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