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Data Science For Beginners | Who Is A Data Scientist? | Data Science Tutorial Using R | Edureka

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** Data Science Certification using R: https://www.edureka.co/data-science **
This Edureka "Data Science for Beginners" PPT talks about the basic concepts of Data Science, which includes machine learning algorithms as well as the roles & responsibilities of a Data Scientist. It also includes a demo using R Studio, that attempts to make sense of all the Data generated in the real world. This PPT talks about the most crucial aspects of data science and covers the following topics:

Why Data Science?
What is Data Science?
Who is a Data Scientist?
What does a Data Scientist do?
How to solve a problem in Data Science?
Data Science Tools
Demo

Check out our Data Science Tutorial blog series: http://bit.ly/data-science-blogs
Check out our complete YouTube playlist here: http://bit.ly/data-science-playlist

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Data Science For Beginners | Who Is A Data Scientist? | Data Science Tutorial Using R | Edureka

  1. 1. Agenda Why Data Science? What is Data Science? Who is a Data Scientist? What does a Data Scientist do? How to solve a problem in Data Science? Data Science Tools Demo
  2. 2. Agenda Why Data Science? What is Data Science? Who is a Data Scientist? What does a Data Scientist do? How to solve a problem in Data Science? Data Science Tools Demo
  3. 3. Why Data Science?
  4. 4. www.edureka.co/data-scienceData Science Certification Course using R Why Data Science? You can make better decisions, you can reduce your production costs by coming out with efficient ways, and give your customers what they actually want! Cost Reduction Faster & Better Decision Making Improved Services and Products Risk Detection
  5. 5. www.edureka.co/data-scienceData Science Certification Course using R Why Data Science? Data Science can help prevent Fraudulent transactions using advanced Machine Learning algorithms and prevent great monetary losses.
  6. 6. What is Data Science?
  7. 7. www.edureka.co/data-scienceData Science Certification Course using R What is Data Science? Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data. DATA SCIENCE Analysis Structure Algorithm Process Programming Insight
  8. 8. www.edureka.co/data-scienceData Science Certification Course using R What is Data Science? It is an inter-disciplinary field deploying scientific methods, processes and systems to gain insight from data in various forms. Tell us something we don’t know already. Statistics Code Business
  9. 9. www.edureka.co/data-scienceData Science Certification Course using R What is Data Science? How is this different from what statisticians have been doing for years? Business Administration Exploratory Data Analysis Machine Learning & Advanced Algorithms Data Product Engineering Business Analyst Data Scientist
  10. 10. Who is Data Scientist?
  11. 11. www.edureka.co/data-scienceData Science Certification Course using R Who is a Data Scientist?
  12. 12. www.edureka.co/data-scienceData Science Certification Course using R Who is a Data Scientist? Statistics Discrete Theory Combinatorics Decision Theory Machine Learning
  13. 13. www.edureka.co/data-scienceData Science Certification Course using R Who is a Data Scientist?
  14. 14. www.edureka.co/data-scienceData Science Certification Course using R Who is a Data Scientist? Economics Finance Operations Management Business Intelligence
  15. 15. www.edureka.co/data-scienceData Science Certification Course using R Who is a Data Scientist?
  16. 16. www.edureka.co/data-scienceData Science Certification Course using R Who is a Data Scientist? Computer Science Software Engineering Systems Development
  17. 17. What does a Data Scientist do?
  18. 18. www.edureka.co/data-scienceData Science Certification Course using R Processing & Cleansing Data What does a Data Scientist do? Data Mining Building Prediction Models Extending Data Optimizing and building classifiers using Machine Learning
  19. 19. www.edureka.co/data-scienceData Science Certification Course using R Processing & Cleansing Data What does a Data Scientist do? Data Mining Building Prediction Models Extending Data Optimizing and building classifiers using Machine Learning
  20. 20. www.edureka.co/data-scienceData Science Certification Course using R What does a Data Scientist do? Data Mining Processing & Cleansing Data Building Prediction Models Extending Data Optimizing and building classifiers using Machine Learning
  21. 21. www.edureka.co/data-scienceData Science Certification Course using R What does a Data Scientist do? Data Mining Processing & Cleansing Data Building Prediction Models Extending Data Optimizing and building classifiers using Machine Learning
  22. 22. www.edureka.co/data-scienceData Science Certification Course using R What does a Data Scientist do? Data Mining Processing & Cleansing Data Building Prediction Models Extending Data Optimizing and building classifiers using Machine Learning
  23. 23. www.edureka.co/data-scienceData Science Certification Course using R What does a Data Scientist do? Data Mining Processing & Cleansing Data Building Prediction Models Extending Data Optimizing and building classifiers using Machine Learning
  24. 24. How to solve a problem in Data Science?
  25. 25. www.edureka.co/data-scienceData Science Certification Course using R How to solve a problem in Data Science? 3 62 41 5 Discovery Data Preparation Model Planning Model Building Operationalize Communicating Results
  26. 26. www.edureka.co/data-scienceData Science Certification Course using R How to solve a problem in Data Science? 1 3 2 4 Discovery Data Preparation Model Planning Model Building 5 6 Operationalize Communicate ➢ Discovery involves acquiring data from all identifies internal and external resources that can help with a business solution. ➢ You assess if you have the required resources present in terms of people, technology, time and data to support the project.
  27. 27. www.edureka.co/data-scienceData Science Certification Course using R How to solve a problem in Data Science? 1 3 2 4 Discovery Data Preparation Model Planning Model Building 5 6 Operationalize Communicate ➢ In this phase, you require analytical sandbox in which you can perform analytics for the entire duration of the project. ➢ This is what a Sandbox is supposed to look like; ➢ ETLT means to Extract, Transform, Load and Transform. Preparing the Analytics Sandbox Performing ETLT Data Conditioning Survey & Visualize
  28. 28. www.edureka.co/data-scienceData Science Certification Course using R How to solve a problem in Data Science? 1 3 2 4 Discovery Data Preparation Model Planning Model Building 5 6 Operationalize Communicate ➢ You will apply Exploratory Data Analytics (EDA) using various statistical formulas and visualization tools. Common Tools for Model Planning R SAS/ ACCESS SQL Service Analysis Services
  29. 29. www.edureka.co/data-scienceData Science Certification Course using R How to solve a problem in Data Science? 1 3 2 4 Discovery Data Preparation Model Planning Model Building 5 6 Operationalize Communicate ➢ In this phase, you will develop datasets for training and testing purposes. Common Tools for Model Building SAS Miner WEKA SPCS MATLAB Alpine Miner Statistica
  30. 30. www.edureka.co/data-scienceData Science Certification Course using R How to solve a problem in Data Science? 1 3 2 4 Discovery Data Preparation Model Planning Model Building 5 6 Operationalize Communicate ➢ In this phase, you deliver final reports, briefings, code and technical documents. ➢ In addition, sometimes a pilot project is also implemented in a real- time production environment. ➢ This will provide you a clear picture of the performance and other related constraints on a small scale before full deployment.
  31. 31. www.edureka.co/data-scienceData Science Certification Course using R How to solve a problem in Data Science? 1 3 2 4 Discovery Data Preparation Model Planning Model Building 5 6 Operationalize Communicate ➢ You do the following things in this phase; 1. You identify all the key findings 2. communicate to the stakeholders 3. Look for performance constraints, if any 4. determine if the results of the project are a success or a failure
  32. 32. www.edureka.co/data-scienceData Science Certification Course using R How to Choose an Algorithm in Data Science? Is it A or B? Classification Algorithm Is this weird? Anomaly Detection Algorithm How much / How many? Regression Algorithm How is this organised? Clustering Algorithm What should I do next? Reinforcement Learning
  33. 33. www.edureka.co/data-scienceData Science Certification Course using R What is machine Learning? It is a type of Artificial Intelligence that makes the computers capable of learning on their own i.e without explicitly being programmed. With machine learning, machines can update their own code, whenever they come across a new situation.
  34. 34. www.edureka.co/data-scienceData Science Certification Course using R Categories of Algorithm Supervised Learning 1 Supervised Learning is a type of machine learning algorithm that uses a known dataset to make predictions. Unsupervised Learning 2 Unsupervised Learning is a type of machine learning algorithm that uses a input datasets without labelled responses to draw inference. Reinforcement Learning 3 Reinforcement Learning is a type of algorithm inspired by behaviourist psychology, concerned with taking actions to maximise reward.
  35. 35. Data Science Tools
  36. 36. www.edureka.co/data-scienceData Science Certification Course using R Data Science Tools 1. Datasets Hadoop 4 Big Data 3 R programming 2 Spark 55
  37. 37. Demo

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