- Data Science is a multidisciplinary blend of data inference, algorithm development and technology in order to solve analytically complex problems
- Data Science is ultimately about using data in creative ways to generate business values
- A Data Scientist does the exploratory analysis to discover insights from data and uses various advance machine learning algorithms to identify the occurrence of a particular event in the future
- So Data Science is primarily used make decision and predictions
About Smart Pro Data Science
Data Science course has been designed to give learners in-depth knowledge of various data analytics techniques that can be performed. The data science training course also includes various statistical concepts such as linear and logistic regression, cluster analysis and forecasting. Learners will also understand hypothesis testing.
- Work with spreadsheets and analyze data using MS Excel
- Learn how to program with the popular development language, Python
- Learn the basics of social media, mobile technology, analytics, and cloud computing along with an understanding of their interconnectivity
- Learn Cassandra concepts, features, architecture and data model, and how to install, configure and monitor open-source databases.
- Master data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language
- Develop a real-world application using R language.
- course duration 146 hours.
- Learn how the components of the Hadoop ecosystem, such as Hadoop 3.4, Yarn, MapReduce, HDFS, Pig, Impala, HBase, Flume, Apache Spark, and so on. fit in with the Big Data processing lifecycle
- Learn to work with adaptable, versatile frameworks based on the Apache Hadoop ecosystem
- Learn how to build visualizations, organize data, and design dashboards to empower more meaningful business decisions using Tableau Desktop data visualization and reporting tool
- Understand the major aspects of Google Ads network including Search, Display, Mobile, and Video
- Master different techniques in SAS to access and manage data, create data structures, generate reports, and handle errors
- Develop a real-world project using Big Data tools
- course duration 346 hours.
- 2 hours per day, 3 days a week
- The course comprises of recommended practice hours for every module. Students are advised to self practice these hours at lab or home.
- For practice at centre labs the student has to book lab in advance
- Undergraduates/ Graduates
- Working Professionals
- Data Visualizer
- Data Analyst