Course Details

Data Science is changing the way we interact with and explore our world. Because of the increasingly interconnected world, huge amounts of data are being generated and stored every instant. Data Science can be used to transform data into insights that help improve existing processes. Operating costs can be driven down dramatically by effectively incorporating the complex interrelationships in data like never before. This results in better quality assurance, higher product yield and more effective operations.

Data Science is the art of turning data into actions through creating data products. Performing Data Science requires extraction of timely, actionable information from diverse data sources to drive data products.

Machine Learning brings together computer science and statistics to harness that predictive power through detecting patterns in data and adjust actions accordingly. Machine Learning is an approach to achieve Artificial Intelligence (AI) that makes computers able to learn without being explicitly programmed and regulate actions when exposed to new data. Machine learning algorithms are categorized as being supervised or unsupervised. Supervised algorithms apply what has been learned in the past to new data. Unsupervised algorithms draw inferences from datasets.

Our Data Science & Analytics course content is developed and taught by professional Data Scientists with extensive experience in their respective domains in leading multinational companies. Most of these professionals have completed their formal education from prestigious institutions like IIT and IIM and the like. In an attempt to provide a best data science training experience, we review our curriculum frequently and keep updated all the time, to ensure you're learning what's most relevant to employers.

Our Data Science & Analytics course provides practical foundation level training that enables immediate and effective participation in Big Data Analytics projects. This course provides grounding in basic and advanced data analytic methods, machine learning algorithms (supervised & unsupervised),statistical pattern recognition, predictive modelling techniques, tools, technology and analytics project lifecycle. Hands-on sessions with numerous case studies and applications using both R and Python programming, give you an in-depth understanding of how these methods and tools may be applied to real world business challenges that leverage Big Data by a practicing Data Scientist.

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