IMMSInstitute of Management and Social Sciencess
Learn online from the experts
Enhance your learning skills and knowledge with the online courses.
IMSS online courses offers a unique and modern concepts enabling
committed learners to transform their lives
Data Science and Analysis (Beginners Level Course)
| Course Title | : | Data Science and Analysis (Beginners Level Course) |
| Course Duration | : | 2 hours 30 Mins |
| Course Coordinator | : | Dr. Sudipto Ghosh |
| Course Director | : | Dr. Chiranjib Neogi, former Associate Scientist of Indian Statistical Institute |
| Who can Apply | : | Class XII |
| Course Fees | : | Rs. 149/- |
| Last date for applying | : | 20/01/2022 |
| Date of training | : | 2022-01-22 at 5:30 pm |
| Class Platform | : | Google Meet |
| Course Overview | : | Data science can be defined as a blend of mathematics, business acumen, tools, algorithms and machine learning techniques, all of which help us in finding out the hidden insights or patterns from raw data which can be of major use in the formation of big business decisions. We have more data than ever before. But data alone cannot tell us much about the world around us. We need to interpret the information and discover hidden patterns. This is where data science comes in. Data science uses algorithms to understand raw data. The main difference between data science and traditional data analysis is its focus on prediction. Data science seeks to find patterns in data and use those patterns to predict future data. It draws on machine learning to process large amounts of data, discover patterns, and predict trends. Data science includes preparing, analyzing, and processing data. It draws from many scientific fields, and as a science, it progresses by creating new algorithms to analyze data and validate current method |
| Course Description | : | Data Science • Concept of Data Science • Why Data Science • What Is Data Science • Who is a Data Scientist • What Makes Data Science Different • Business Intelligence and Data Science • Looking Backward and Forward • Impact of Data Science • Data Science is Necessary • The Tangible Benefits of Data Products • How Does Data Science Actually Work • Acquiring Data • Preparation of Data • Analysis • Action • Data Science Capability • What Makes a Data Scientist • The Importance of Reason • Analytic Techniques • A Data Science Product • Implementation Constraints • Programming Languages • Job Opportunity as Data Scientist |