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Data Science Course in Bangalore
The professional profile of the data scientist is booming, and, as a result, we have a greater data science course in Bangalore providers available to us who are creating massive number job opportunities to the candidates, both for those who seek to specialize in specific fields with an advanced level and for those who wish to start in the world of data science.
Availabilities and opportunities are more on data science course in bangalore for those who require more flexibility in their training. From the fundamental concepts of autonomous learning (Machine Learning) to specializations in probabilistic models, the offer of online training regarding data science is adapted to all levels and needs. 
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Basic level / beginner
In this first level provides a basic knowledge to get started in data science. In the first approach you will get to know languages ​​and tools used, as well as an explanation of concepts such as Deep Learning or Machine Learning.
·         Specialization in Data Science.   This training program consists of different duration for beginners who want to start in the world of data science. In this approach aims to bring together all the basic concepts that guide data science. 
·         Deep Learning Course.  This is a set of courses framed in the concept of Deep Learning, but that covers practically all the concepts of data science from a basic level, through Machine Learning or NLP. The simplicity of the explanations is one of the strengths of these courses.
·         Machine Learning Foundations: a case study approach.  This course teaches practical cases for most of the typical problems of Machine Learning, such as regressions, predictions or classifications. Well explained. It is the first training course Machine Learning Specialization.
Intermediate level
Although basic concepts of Machine Learning and Deep Learning continue to be addressed, the degree of specialization is greater in this second level. There are courses with more theoretical weight and others focused mainly on the practical part, but all require some prior knowledge.
·         Machine Learning It is a course that covers all the basic concepts of Machine Learning from a theoretical perspective, but without losing the applied point of view. The level is high and it is highly recommended for those who want to begin to know what Machine Learning and its mathematics are, as well as for those who want to refresh some concepts seen in the past. Of course, it takes effort to understand the mathematical details and dedication to perform the practices. 
·         Text Retrieval and Search Engines and Text Mining and Analytics.  Both courses belong to the specialized training program in Data Mining and are a good introduction to the classical techniques of NLP, text analytics, search engines and recommendation systems based on content. In addition, these two courses introduce the vector model of documents, TF-IDF, classification and search engine evaluation techniques, sentiment analysis; document clustering, topics modeling and visualization. They are, without a doubt, a good complement to other NLP courses for Deep Learning that tend to focus on supervised problems.
Practical Deep Learning for Coders. The syllabus is divided into two parts and the         approach is very practical, addressing content ranging from "Embeddings", "Structured Deep Learning", "and Collaborative Filtering “to“Natural Language Processing" or "Generative Adversarial Networks”.
Advanced level / exp
The courses shown here are aimed at professionals who want to expand their training, so that more specific topics and more technical complexity are addressed.
Probabilistic Graphical Models.  A total of three courses ("Representation", "Inference" and "Learning") make up this specialization program on graphic probabilistic models with applications in machine learning and decision models. One of the best aspects is that the exercises (Matlab, Octave) require going down to the detail, which in this case makes it much easier to internalize the theoretical concepts of the inference and learning part.
Deep Learning by Google.  It is an advanced course of introduction to the world of Deep Learning, very complete and that addresses issues at a very low level, so it is perfect for those who want to become professionals.