* Cantinho Satkeys

Refresh History
  • yaro-82: 1994
    07 de Setembro de 2025, 16:49
  • FELISCUNHA: Votos de um santo domingo para todo o auditório  43e5r6
    07 de Setembro de 2025, 10:52
  • j.s.: tenham um excelente fim de semana  49E09B4F
    06 de Setembro de 2025, 17:07
  • j.s.: dgtgtr a todos  4tj97u<z
    06 de Setembro de 2025, 17:07
  • FELISCUNHA: Boa tarde pessoal  49E09B4F bom fim de semana  htg6454y
    05 de Setembro de 2025, 14:53
  • JPratas: try65hytr A Todos  4tj97u<z classic k7y8j0
    05 de Setembro de 2025, 03:10
  • cereal killa: dgtgtr pessoal  4tj97u<z
    03 de Setembro de 2025, 15:26
  • FELISCUNHA: ghyt74  pessoal   49E09B4F
    01 de Setembro de 2025, 11:36
  • j.s.: de regresso a casa  535reqef34
    31 de Agosto de 2025, 20:21
  • j.s.: try65hytr a todos  4tj97u<z
    31 de Agosto de 2025, 20:21
  • FELISCUNHA: ghyt74   49E09B4e bom fim de semana  4tj97u<z
    30 de Agosto de 2025, 11:48
  • henrike: try65hytr     k7y8j0
    29 de Agosto de 2025, 21:52
  • JPratas: try65hytr Pessoal 4tj97u<z 2dgh8i classic k7y8j0
    29 de Agosto de 2025, 03:57
  • cereal killa: dgtgtr pessoal  2dgh8i
    27 de Agosto de 2025, 12:28
  • FELISCUNHA: Votos de um santo domingo para todo o auditório  4tj97u<z
    24 de Agosto de 2025, 11:26
  • janstu10: reed
    24 de Agosto de 2025, 10:52
  • FELISCUNHA: ghyt74   49E09B4F  e bom fim de semana  4tj97u<z
    23 de Agosto de 2025, 12:03
  • joca34: cd Vem dançar Kuduro Summer 2025
    22 de Agosto de 2025, 23:07
  • joca34: cd Kizomba Mix 2025
    22 de Agosto de 2025, 23:06
  • JPratas: try65hytr A Todos e Boas Férias 4tj97u<z htg6454y k7y8j0
    22 de Agosto de 2025, 04:22

Autor Tópico: Complete Time Series Data Analysis Bootcamp In R  (Lida 338 vezes)

0 Membros e 1 Visitante estão a ver este tópico.

Offline mitsumi

  • Sub-Administrador
  • ****
  • Mensagens: 124987
  • Karma: +0/-0
Complete Time Series Data Analysis Bootcamp In R
« em: 03 de Março de 2020, 05:44 »

Complete Time Series Data Analysis Bootcamp In R
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 5h 27m | 4.15 GB
Instructor: Minerva Singh

Learn How To Work With Time Series/Temporal Data Using Statistical Modelling & Machine Learning Techniques In R

What you'll learn

Implement Common Data Cleaning And Visualization Techniques In R
Be Able To Read In, Pre-process & Visualize Time Series Data
The Basic Conditions Time Series Data Must Fulfill & How To Check For These
Model Time Series Data To Forecast Future Values
Use Machine Learning Regression For Forecasting Future Values
Detect Sudden Changes In The Values During A Given Time Period

Requirements

Prior Familiarity With The Interface Of R & R Studio
Prior Experience Of Applying Basic Statistical Techniques (Such As The Calculation Of Averages) To Data
Be Able To Carry Out Data Reading And Pre-Processing Tasks Such As Visualization In R
Interest In Working With Time Series Data Or Data With A Time Component To Them

Description

THIS IS YOUR COMPLETE GUIDE TO TIME SERIES DATA ANALYSIS IN R!

This course is your complete guide to time series analysis using R. So, all the main aspects of analyzing temporal data will be covered n depth..

If you take this course, you can do away with taking other courses or buying books on R based data analysis. 

In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By becoming proficient in in analyzing time series data in R, you can give your company a competitive edge and boost your career to the next level.

LEARN FROM AN EXPERT DATA SCIENTIST WITH +5 YEARS OF EXPERIENCE:

Hey, my name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University.

I have +5 years of experience in analyzing real life data from different sources  using data science related techniques and i have produced many publications for international peer reviewed journals.

 Over the course of my research I realized almost all the R data science courses and books out there do not account for the multidimensional nature of the topic .

So, unlike other R instructors, I dig deep into the data science features of R and gives you a one-of-a-kind grounding in data science related topics!

You will go all the way from carrying out data reading & cleaning  to to finally implementing powerful statistical and machine learning algorithms for analyzing time series data.

Among other things:

You will be introduced to powerful R-based packages for time series analysis.
You will be introduced to both the commonly used techniques, visualization methods and machine/deep learning techniques that can be implemented for time series data.
& you will learn to apply these frameworks to real life data including temporal stocks and financial data. 

NO PRIOR R OR STATISTICS/MACHINE LEARNING KNOWLEDGE IS REQUIRED!

You'll start by absorbing the most valuable R Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R.

My course will help you implement the methods using REAL DATA obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real-life.

After taking this course, you'll easily use the common time series packages in R...

You'll even understand the underlying concepts to understand what algorithms and methods are best suited for your data.

We will work with real data and you will have access to all the code and data used in the                                                                                                                                                                                                course.

Who this course is for:

Anyone Who Wants Master Time Series Data In R
Anyone Who Wants To Become Proficient In Time Series Data Analysis Working With Real Life Data
Anyone Who Wants To Become An Expert Data Scientist


Download link:
Só visivel para registados e com resposta ao tópico.

Only visible to registered and with a reply to the topic.

Links are Interchangeable - No Password - Single Extraction