< SSAML2019
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Summer School Cum Internship Program on
Data Science and AI
02-23 June. 2019

Organized by: NextDataScience
Theme: Applied Machine Learning, Deep Learning and Big Data Analytics
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Objective of the SSAML2019:

1. The objective is to familiarize the audience with some basic learning algorithms and techniques and their applications, as well as general questions related to analyzing and handling large data sets.
2. Several libraries and data sets are publicly available, that will be used to illustrate the application of machine learning and deep learning algorithms.
3. The emphasis will be on machine learning algorithms and applications, with some broad explanation of the underlying principles.
4. To develop the basic skills necessary to pursue research in machine learning, deep learning and big data analytics.
5. To develop the design and programming skills that will help you to build intelligent, adaptive artifacts.
6. The emphasis will be on big data tools and technologies like hadoop, spark, pig, hive, sqoop, hbase and applications, with some broad explanation of the underlying principles.
7. To gain the skills to be a data scientist or planning to shift your career in data science and analytics domain

Learning outcomes of the SSAML2019:

After completing the study of the discipline “Machine Learning ”, the participants are expected to:
1. Understand complexity of Machine Learning and Deep Learning algorithms and their limitations;
2. Understand modern notions in data analysis oriented computing;
3. Be capable of confidently applying common Machine Learning algorithms in practice and implementing their own;
4. Be capable of performing experiments in Machine Learning and Deep Learning using real-world data.
5. Be capable to integrate machine learning libraries and mathematical and statistical tools with modern technologies like hadoop and mapreduce
6. Be capable to select and implement machine learning techniques and computing environment that are suitable for the applications under consideration
7. Be capable to identify the characteristics of datasets and compare the trivial data and big data for various applications
8. Be capable of performing distributed computations.
9. Be capable of performing experiments with hadoop, pig, hive, sqoop using real-world data.

Internship Opportunity: Participants can avail summer internship opportunity at next data science.