Program Description and Objectives
- Applications of Big Data transcend disciplines. Use of predictive analytics pervades diverse disciplines as oil and gas, marketing and sales, sports, molecular biology, drug-designing, waste management, finance and the list is very long. Smart cities, for example, are the melting pot where variety of big data technologies, mesh with one another to transform a city into a semi-intelligent being.
- In Marketing and Sales, Big Data is fast emerging as a potent tool to gain deeper insights into Customer behavior and thereby act as a strong driver in spurring innovation.
- In manufacturing, operations managers are employing advanced analytics on historical process data to identify patterns and relationships among discrete process steps and inputs, and then optimize the factors that prove to have the greatest effect on yield.
- Broadly, the course has two parts: one the analytics part and second the technological part. The analytics part is about learning machine learning algorithms and implementing them, the technological part is about learning to work in Hadoop ecosystem including NoSQL databases. At the end of this course, given a large dataset from any domain, a participant should:
- Be able to clean and transform/process the dataset to make it ready for analysis
- Be able to select a subset of appropriate machine learning algorithms that could be applied to get the desired predictive results
- Gain sufficient proficiency in tools necessary to implement algorithms
- Finally, put to use the tools and techniques to get a reasonable predictive accuracy
This course is project oriented: All tools and data, including Hadoop-ecosystem, necessary for learning data-analytics are provided to the participants in advance.
Who should attend
Data being ubiquitous, the program cuts-across job or academic profiles. The techniques taught are generic in nature. These will be valuable to anyone who wishes to interpret data to advance his knowledge and insights of environment. Specifically, the course will be useful to:
- Executives -Ambitious Executives (from Private/Public sectors) looking forward to sharpening their skills in making sense of data in order to innovate and add more value to their organization and to society.
- Academicians -Lecturers and Professors for extending the horizon of their knowledge through deepening their research skills.
- Data Scientists/ Developers -Techniques taught to them will have applications in a broad array of disciplines.
- Students/Research Scholars -IInd year students currently enrolled in Engineering / PGDM/ MBA or any graduate or post graduate program that have had an introductory course in statistics. These students can look forward to better placement opportunities with added skill set.
The Data Analytics program is Project based not Pure Theory-based but learning with question/answers are in real-time: Live Virtual Interactive Learning. Algorithms are first explained conceptually, avoiding mathematics and then these are implemented with real data from Industry as Projects. Datasets for implementation are made available in advance and so also a copy of code to be executed. The code is numbered and copiously commented so that long after the lecture has finished, students can go back through the code/comments and refresh their knowledge. During the lecture, code is explained and executed line-by-line. At his end the student also executes it. Consequently, results are available at our end as also on Students Laptop. The whole experience is as if everyone is sitting together in a lab.
Two Sessions of 3 hours per week on Sat-Sun.
Saturday - 10:30 AM to 01:30 PM
Sunday - 10:30 AM to 01:30 PM
Based on Performance in Exercises & Projects
The sessions will be delivered on Growth Factories Growth Factories interactive learning platform.
Course material will be shared either through cloud or in hard copy with all the participants at the appropriate time.