Monday, 8 October 2018

DATA SCIENCE COMING UP STATE-OF-THE ART LEARNING TRAIL (draft)


SOURCE: ACTION RESEARCH FORUM

https://www.bing.com/videos/search?q=METADATA&view=detail&mid=E0BBB937040C3E5D03DAE0BBB937040C3E5D03DA&FORM=VIRE POWERRPOINT

 







LEARN SPSS:




Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining.


TSQL, MICROSOFT EXCEL, POWER BI, PYTHON, R, AZURE MACHINE LEARNING, HDISIGHT, SPARK.


Track detail

Each course runs for three months and starts at the beginning of a quarter. January—March, April—June, July—September, and October —December. The capstone runs for four weeks at the beginning of each quarter: January, April, July, October. For exact dates for the current course run, please refer to the course detail page on edX.org.
* Courses can be taken during any course run and in any order. When multiple course options are listed for a skill, only one must be completed to satisfy the requirements for graduation.


Analyze And Visualize Data

Option-1

Learn how to connect and visualize your data with Microsoft Power BI. Find out how to import your data, author reports using Power BI Desktop, and publish those reports to the Power BI service. Create dashboards and share with business users on the web and on mobile devices.
Option-2
Explore tools in Excel that enable the analysis of more data than ever before, with improved visualizations and more sophisticated business logic. Learn how to import data from different sources, create mashups between data sources, and prepare data for analysis.
Communicate Data Insights

Analytics Storytelling for Impact Provided by Microsoft

Learn effective strategies and tools to master data communication in the most impactful way possible—through well-crafted analytics stories. Find out how stories create value and why they matter. Learn to craft stories, command the room, finish strong, and assess your impact. Get practical help applying these ideas to your data analytics work. Plus, you'll learn guidelines and best practices for creating high-impact reports and presentations.
Apply Ethics And Law In Analytics
Learn to apply ethical and legal frameworks to initiatives in the data profession. You will explore practical approaches to data and analytics problems posed by work in Big Data, Data Science, and AI. You will also investigate applied data methods for ethical and legal work in Analytics and AI.
Querying Data with Transact-SQL; Provided by Microsoft
From querying and modifying data in SQL Server or Azure SQL to programming with Transact-SQL, learn essential skills that employers need.

Query Relational Data

Querying Data with Transact-SQL
; Provided by Microsoft
From querying and modifying data in SQL Server or Azure SQL to programming with Transact-SQL, learn essential skills that employers need.

Explore Data with Code
Option-1
Introduction to R for Data Science; Provided by Microsoft
Learn the basics of R programming. Starting from variables and basic operations, you will eventually learn how to handle data structures such as vectors, matrices, data frames and lists. In the final section, you will dive deeper into the graphical capabilities of R, and create your own stunning data visualizations. No prior knowledge in programming or data science is required.
Option-2
Learn the basics of Python programming. Starting from the very beginning, with basic arithmetic and variables, and learn how to handle data structures, such as Python lists, Numpy arrays, and Pandas DataFrames. Along the way, you’ll learn about Python functions and control flow. Plus, you’ll look at the world of data visualizations with Python and create your own stunning visualizations based on real data.
Apply Math and Statistics to Data Analysis;  
Option-1
Learn the essential mathematical foundations for machine learning and artificial intelligence using R. The course focuses on mathematical concepts that you’ll encounter in studies of machine learning. It is designed to fill the gaps for students who missed these key concepts as part of their formal education, or who need to refresh their memories after a long break from studying math.
Option-2
Learn the essential mathematical foundations for machine learning and artificial intelligence using Python. The couse focuses on mathematical concepts that you’ll encounter in studies of machine learning. It is designed to fill the gaps for students who missed these key concepts as part of their formal education, or who need to refresh their memories after a long break from studying math.

Option-3
Gain a solid understanding of statistics and basic probability, using Excel, and build on your data analysis and data science foundation.
Plan and Conduct Data Studies;
Option-1
Learn the essential skills and hands-on experience with the science and research aspects of data science work using R, from setting up a proper data study to making valid claims and inferences from data experiments.
Option-2
Learn the essential skills and hands-on experience with the science and research aspects of data science work using Python, from setting up a proper data study to making valid claims and inferences from data experiments.
Build Machine Learning Models;
Option-1
Get hands-on experience building and deriving insights from machine learning models using R and Azure Notebooks.
Option-2
Get hands-on experience building and deriving insights from machine learning models using Python and Azure Notebooks.
BUILD PREDICTIVE SOLUTIONS AT SCALE
Option-1
Learn how to build predictive web services for Big Data workflows using Azure Machine Learning.
Option-2
Analyzing Big Data with Microsoft R; Provided by Microsoft
Learn how to use Microsoft R Server to analyze large datasets using R, one of the most powerful programming languages.

Option-3
Learn how to use Spark in Microsoft Azure HDInsight to create predictive analytics and machine learning solutions. Find out how to cleanse and transform data, build machine learning models, and create real-time machine learning solutions using Python, Scala, and R with Apache Spark.

FINAL PROJECT
Showcase the knowledge and skills you've acquired during the Microsoft Professional Program for Data Science, and solve a real-world data science problem in this program capston e project. The project takes the form of a challenge in which you will explore a dataset and develop a machine learning solution that is tested and scored to determine your grade. Note: This course assumes you have completed the previous courses in the Microsoft Professional Program for Data Science.
Microsoft Professional Program Certificate in Data Science

MACHINE LEARNING: 
https://www.google.com/search?rct=j&q=MACHINE%20LEARNING


Machine learning

Field of study
Machine learning is an interdisciplinary field that uses statistical techniques to give computer systems the ability to "learn" from data, without being explicitly programmed. The name machine learning was coined in 1959 by Arthur Samuel. Wikipedia

Image result for HILL CLIMBING ALGORITHM

NOTE: WHETHER HILL CLIMBING ALGO.IIRTHM VS MACHINE LEARNING  A SUCCESS TRAIL FOR PROJECT EVALUATION? 

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