Data Science has been a trending field of study in various industries in today’s era, because of the tremendous increase in data generation with high velocity. Soon every business sector started building new strategies to make huge profits from the data being generated. Here comes the role of data scientist who not only drives meaningful insights out of huge and complex data but also he/she should have the strong domain knowledge, should be flexible enough to use different tools as when needed and updated with skills to remain valuable assets to their organizations. To become a professional Data Scientist, you must have a strong hold on domain knowledge, statistics, programming, data interpretation, and communication skills.
Data science competitional/informational websites to follow: Kaggle , Stanford Online , crowdAnalytix , KDnudggets , AnalyticsVidhya , EliteDataScience , statistics , simplystats
Let us see the 10 most used tools for Data Scientists in the order of their preference:
Tensorflow:
It is an open source software library works as a machine learning framework, especially used for building neural nets in machine learning applications. It was developed by Google for internal use and later released under the Apache 2.0 open source license on November 9, 2015.Official site: https://www.tensorflow.org
Repository: https://github.com/tensorflow/tensorflow
Websites to follow: Tensorflow, learningtensorflow, Python Deep LearningTutorialspoint, pythonprogramming
Python:
Course: Data Scientist with Python
Official site: https://www.python.org
Documentations: Python 3.7.0 and Python 2.7.15
Websites to follow: realpython, Analytics Vidhya, Python Tutorialspoint, Python-datascience Handbook
R:
It is open-source, graphics supported and statistical programming language. It was developed by R Core Team, designed by Ross Ihaka and Robert Gentleman and released under the GNU GPL
v2 License on August 1993.
Course: Data Scientist with R
Official site: https://www.r-project.org
Documentation: R-Manuals
Websites to follow: Rbloggers , RStudio Blog
Spark - MLlib:
MLlib is Apache Spark's scalable machine learning library. Machine Learning Library (MLlib) Guide
It was developed by Apache Software Foundation, UC Berkeley, AMPLab, Databricks and released under Apache License 2.0 License on May 26, 2014.
Spark API Docs:
Official site: https://spark.apache.org/mllib/
Repository: https://github.com/apache/spark
Websites to follow: Dataflair , Apache Spark Tutorialspoint, datacamp
Hadoop(MapReduce):
Commercial distributions of Hadoop are currently offered by four primary vendors of big data platforms: Amazon Elastic MapReduce, Cloudera CDH Hadoop Distribution, Hortonworks Data Platform (HDP) and MapR Hadoop Distribution.
It was developed by Apache Software Foundation, and released under Apache License 2.0 License on December 10, 2011.
Official site: http://hadoop.apache.org
Repository:https://git-wip-us.apache.org/repos/asf?p=hadoop.git
Websites to follow: Dataflair , Hadoop Tutorialspoint , Yahoo developer Network, guru99
Amazon web services:
It was released under its parent company Amazon on March 2006.
Courses:
Official site: https://aws.amazon.com/
Documentations: AWS Guides and API References
Websites to follow: AWS Tutorialspoint, cloudacademy , guru99
Jupyter Notebooks:
Official site: https://jupyter.org/index.html
Installation: Installing the Jupyter Notebook
Documentation: Jupyter Interactive Notebook
Websites to follow: codecademy, datacamp
Microsoft Azure Machine Learning:
Official site: https://azure.microsoft.com/en-us/
Product: Azure Machine Learning Studio
Documentation: Azure Machine Learning Services documentation
Websites to follow: Azure Tutorialspoint, datasciencedojo, cloudacademy
Tableau:
It is a data visualization product for creating storytelling dashboards which focus on business intelligence. It was founded by Christian Chabot, Chris Stolte,Pat Hanrahan at Mountain View, California(2003), and released as Public company in January 2003.
Official site: https://www.tableau.com
Websites to follow: Tableau Training, Tableau Tutorialspoint
SQL:
Official site: https://www.sas.com/en_in/home.html
Courses: SQL - MySQL for Data Analytics and Business Intelligence , SQL for Data Science
Websites to follow: W3Schools, SQL Tutorialspoint, SQL Cheat Sheet
SAS:
Statistical Analysis System used for advanced analytics, statistical multivariate analysis, data management, Business Intelligence, graphical data representation, and predictive data modeling.It was developed by SAS Institute, and released under Proprietary License in the year 1976.
SAS also provides Academic Programs like Free SAS e-Learning.
Official site: www.sas.com
Documentation: SAS 9.4 and SAS Viya 3.4 Programming Documentation
Websites to follow: support.sas.com, blogs.sas.com, SAS Tutorialspoint, KentState, SAS Global Forum
Excel:
Microsoft Excel is a spreadsheet used for calculations, pivot tables, graphical representation tools, and supports macro programming language known as visual basic for applications.
It was developed by Microsoft, and released under Trialware License in the year 1987.
It was developed by Microsoft, and released under Trialware License in the year 1987.
Official site: office.microsoft.com
Websites to follow: MSExcel Tutorialspoint, Microsoft Excel Help Center, GCFGlobal, Excel Exposure, Contextures, Chandoo.org
Top best Certification courses on Data Science:
- Machine Learning, created by Stanford University on Coursera.
- Deep Learning Specialization by Andrew Ng’s deeplearning.ai on Coursera.
- Data Scientist Nanodegree program by Udacity.
- Machine Learning A-Z™: Hands-On Python & R In Data Science, created by Kirill Eremenko, Hadelin de ponteves, SuperDataScience Team, SuperDataScience Support
- Edx Data Science Courses by top Universities and Institutions on Edx.org
- Data Scientist Masters Program, by Simplilearn Course advisors: Ronald van Loon, Mike Tamir
- Free Online Courses in Data Science by Class Central.
- Analytics training courses by Experfy.
- Data Science Courses by FutureLearn. FutureLearn offers online maths, science and engineering courses created by experts from leading universities and organisations. Also helps learners brush up on basic science and numeracy skills or master advanced topics like robotics and forensics.
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