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    Business Analytics with Excel | Data Science Tutorial | Simplilearn



    Business Analytics with excel training has been designed to help initiate you to the world of analytics. For this we use the most commonly used analytics tool i.e. Microsoft Excel. The training will equip you with all the concepts and hard skills required to kick start your analytics career. If you already have some experience in the IT or any core industry, this course will quickly teach you how to understand data and take data driven decisions relative to your domain using Microsoft excel.

    Data Science Certification Training - R Programming: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Data-Excel-W3vrMSah3rc&utm_medium=SC&utm_source=youtube

    For a new-comer to the analytics field, this course provides the best required foundation. The training also delves into statistical concepts which are important to derive the best insights from available data and to present the same using executive level dashboards. Finally we introduce Power BI, which is the latest and the best tool provided by Microsoft for analytics and data visualization.

    What are the course objectives?
    This course will enable you to:
    1. Gain a foundational understanding of business analytics
    2. Install R, R-studio, and workspace setup. You will also learn about the various R packages
    3. Master the R programming and understand how various statements are executed in R
    4. Gain an in-depth understanding of data structure used in R and learn to import/export data in R
    5. Define, understand and use the various apply functions and DPLYP functions
    6. Understand and use the various graphics in R for data visualization
    7. Gain a basic understanding of the various statistical concepts
    8. Understand and use hypothesis testing method to drive business decisions
    9. Understand and use linear, non-linear regression models, and classification techniques for data analysis
    10. Learn and use the various association rules and Apriori algorithm
    11. Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering

    Who should take this course?
    There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals:
    IT professionals looking for a career switch into data science and analytics
    Software developers looking for a career switch into data science and analytics
    Professionals working in data and business analytics
    Graduates looking to build a career in analytics and data science
    Anyone with a genuine interest in the data science field
    Experienced professionals who would like to harness data science in their fields

    Who should take this course?
    There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals:
    1. IT professionals looking for a career switch into data science and analytics
    2. Software developers looking for a career switch into data science and analytics
    3. Professionals working in data and business analytics
    4. Graduates looking to build a career in analytics and data science
    5. Anyone with a genuine interest in the data science field
    6. Experienced professionals who would like to harness data science in their fields

    For more updates on courses and tips follow us on:
    - Facebook : https://www.facebook.com/Simplilearn
    - Twitter: https://twitter.com/simplilearn

    Get the android app: http://bit.ly/1WlVo4u
    Get the iOS app: http://apple.co/1HIO5J0

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    Data Science and Big Data Analytics: Making Data-Driven Decisions



    Discover how to turn big data into even bigger results in our seven-week digital course from MIT. For more info, visit https://bigdataanalytics.mit.edu/

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    Cloudera: Instrumented Data Analytics



    Sizing clusters for jobs, finding bottlenecks or getting insight into failures after they have run in Apache Spark isn't easy. In this episode of 'This is My Architecture' - https://amzn.to/2MCyvh1, Wing from Cloudera explains how they use telemetry to optimize analytics workloads on AWS to make those headaches disappear.

    Host: Adrian De Luca, Solution Architect, AWS
    Speaker: Wing Leong Ho, Senior Sales Engineer, Cloudera

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    Smart Data Analytics: Die BMW Group setzt auf intelligente Nutzung von Produktionsdaten.



    Bei der Produktion eines Automobils entstehen entlang der gesamten Wertschöpfungskette erhebliche Mengen an Daten. Die BMW Group analysiert in ihrem Digitalisierungsfeld Smart Data Analytics diese Daten zielgerichtet zur Weiterentwicklung ihres Produktionssystems. In allen Fertigungsbereichen und der Logistik leisten die Erkenntnisse aus intelligenten Datenanalysen einen wirksamen Beitrag zur Verbesserung der Qualität. Dank der vernetzten Produktion steigt die Anlagenverfügbarkeit spürbar: jede gewonnene Minute bedeutet ein zusätzlich gebautes Fahrzeug.

    Mehr Informationen:
    https://www.bmwgroup.com/produktion

    Abonniere den offiziellen BMW Group YouTube Channel unter https://www.youtube.com/user/BMWGroupView

    Folge uns auf Facebook:
    https://www.facebook.com/BMWGroup

    Instagram: https://www.instagram.com/bmwgroup

    Twitter:
    https://twitter.com/BMWGroup

    Google+:
    https://plus.google.com/+BMWGroup

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    Teradata Indonesia: Tawarkan Solusi Binis Lewat Big Data Analytics



    Sudah lebih dari dua tahun, teknologi cloud telah memberikan penetrasi yang tinggi di Indonesia, terutama di kalangan enterprise. Kemudian, hadirlah big data dengan sistem data analytics mampu membantu para pembuat keputusan di perusahaan untuk memberikan keputusan bisnis yang lebih cepat dan akurat.

    See More Videos On Tekno TV:
    www.teknopreneur.com/tekno-tv

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    Learning Predictive Analytics With Python, Analyzing Election Data With Pandas [Python Statistics]



    IN this Exploratory Data Analysis Tutorial, We perform predictive analytics with python by analyzing Election data from 2 candidates. Pandas data Analysis Techniques are used to learn about patterns in the election data. This is a Part of Python with Statistics Tutorial series.

    🔷🔷🔷🔷🔷🔷🔷

    Jupyter Notebooks and Data Sets for Practice: https://github.com/theengineeringworld/statistics-using-python

    🔷🔷🔷🔷🔷🔷🔷

    Python Graph Visualization, Statistics For Data Analytics [ Python Bar Graph Example Tutorial ] https://youtu.be/3KofFIhtjNE

    Data Cleaning Steps and Methods, How to Clean Data for Analysis With Pandas In Python [Example] 🐼 https://youtu.be/GMxCL0PBHzA

    Data Wrangling With Python Using Pandas, Data Science For Beginners, Statistics Using Python 🐍🐼 https://youtu.be/tqv3sL67sC8

    Cleaning Data In Python Using Pandas In Data Mining Example, Statistics With Python For Data Science https://youtu.be/xcKXmXilaSw

    Cleaning Data In Python For Statistical Analysis Using Pandas, Big Data & Data Science For Beginners https://youtu.be/4own4ojgbnQ

    Exploratory Data Analysis In Python, Interactive Data Visualization [Course] With Python and Pandas https://youtu.be/VdWfB30QTYI

    Python Describe Statistics, Exploratory Data Analysis Using Pandas & NumPy [Descriptive Statistics] https://youtu.be/6SeJH0p7n44

    Data Visualization In Python, [ Plots Of Two Variables ] Statistics & Data Analysis With Python 🐍 https://youtu.be/uufMAMUEAaQ

    Python Graph Visualization, Exploratory Data Analysis With Pandas & Matplotlib [ Python Statistic ] https://youtu.be/Eb9eD4aNS7o

    Python Data Visualization [ Graphing Categorical Data ] Pandas Data Analysis & Statistics Tutorial https://youtu.be/M1h0pPFVy0E

    Exploratory Data Analysis In Python, Email Analytics With Pandas [ Predictive Analytics Python ] 🔴 https://youtu.be/03OJrdbhor0

    Learning Predictive Analytics With Python, Analyzing Election Data With Pandas [Python Statistics] https://youtu.be/sNg8VnMOAfw

    🔷🔷🔷🔷🔷🔷🔷

    *** Complete Python Programming Playlists ***

    * Python Data Science
    https://www.youtube.com/watch?v=Uct_EbThV1E&list=PLZ7s-Z1aAtmIbaEj_PtUqkqdmI1k7libK

    * NumPy Data Science Essential Training with Python 3
    https://www.youtube.com/playlist?list=PLZ7s-Z1aAtmIRpnGQGMTvV3AGdDK37d2b

    * Python 3.6.4 Tutorial can be fund here:
    https://www.youtube.com/watch?v=D0FrzbmWoys&list=PLZ7s-Z1aAtmKVb0fpKyINNeSbFSNkLTjQ

    * Python Smart Programming in Jupyter Notebook:
    https://www.youtube.com/watch?v=FkJI8np1gV8&list=PLZ7s-Z1aAtmIVV0dp08_X-yDGrIlTExd2

    * Python Coding Interview:
    https://www.youtube.com/watch?v=wwtzs7vTG50&list=PLZ7s-Z1aAtmJqtN1A3ydeMk0JoD3Lvt9g

    📌📌📌📌📌📌📌📌📌📌

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    Big Data Analytics: Answers from Big Data



    Keynote video, presented at the SAS Analytics Conference 2012, by William Hakes, CEO and Co-Founder of Link Analytics.

    Big Data Analytics is not just hype.
    Big Data Analytics is more than technology. It's a new way of thinking.
    Here's proof as to why we need Big Data Analytics:
    In 2012, the world's information totaled over 2 zetabyes. That's 2 trillion gigabytes.
    By 2020, that number will be 35 trillion.
    80% of this new data is unstructured.
    It is too large, too complex, and too disorganized to be analyzed by traditional tools.
    We need new tools and new talent to navigate this information and find value.
    We are at the beginning of the Big Data Revolution.
    Are YOU ready?

    www.linkanalytics.com

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    Big Data Analytics: Aktuelle Trends, Technologien und Lösungen



    White Papers, Demos und Webinare unter http://www.sas.de

    Alexander Bruder (SAS Deutschland) spricht mit den Experten Andreas Diggelmann (SAS International), Klaus Fabits und Dr. Andreas Becks (SAS DACH) über aktuelle Fragestellungen, Trends und Entwicklungen zu den Themen Datenvisualisierung, Analytics in der Cloud und für Hadoop, Customer Experience Management, Risikomanagement und mehr.

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