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Learn how to Solve real World Business Problems. ,Build Time Series Models for Time Series Analysis & Forecasting

What you will learn

Carry out time-series analysis in Python and interpreting the results, based on the real world challenges

Forecast the future based on patterns observed in the past.

Gain Hands-on by solving Real World challenges

Comprehend stationarity and how to perform Stationary Test

Description

Are you looking to land a top-paying job in Data Science , AI & Time Series Analysis & Forecasting?

Or are you a seasoned AI practitioner who want to take your career to the next level?

Or are you an aspiring data scientist who wants to get Hands-onΒ  Data Science and Time Series Analysis?

If the answer is yes to any of these questions, then this course is for you!

This course will teach you the practical skills that would allow you to land a job as a quantitative financial analyst, a data analyst or a data scientist.

In business, Data Science , AIΒ  is applied to optimize business processes, maximize revenue and reduce cost. The purpose of this course is to provide you with knowledge of key aspects of data science & Time Series applications in business in a practical, easy and fun way. The course provides students with practical hands-on experience using real-world datasets.


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Welcome to the best online resource for learning how to use the Python programming Language for Time Series Analysis!

This course will teach you everything you need to know to use Python for forecasting time series data to predict new future data points.

1.Task #1 @Predict closing Price of BitcoinΒ  : Develop an Time Series model to predict closing price of Bitcoin

2.Task #2 @Predict Number of Births: Develop Time Series Model to predict number of births on a particular day…

3.Task #3 @Predict the Stock Prices: Predict the prices of stock using Facebook Prophet..

English
language

Content

Introduction
Intro to this course & course Benefits
How to follow this course-must watch
How to download Anaconda Navigator & do set-up
Quick Summary of Jupyter Notebook
Project 1–>> Predict the prices of a Bitcoin
Introduction to Business Problem
Dataset & resources
Prepare your data for Analysis
What is re-sampling & how to perform it..
Perform In-depth Analysis on Data..
What is trend & how to analyse trend of closing price..
Building a Base-line Model..
What is seasonality & stationarity & how to examine it.
Performing Statistical Test to detect Stationarity..
How to Smoothen your series
Build model using Facebook Prophet
How to cross validate your Facebook Prophet model..
Project 2–>> Predict Number of Births on a given day
Dataset & resources
Understanding distribution & trend of data..
What is rolling & how to perform rollling on our data..
Building a naive model & evaluate it..
Intuition behind ARIMA –part 1
Intuition behind MA Model– ARIMA part 2
Intuition behind AR model — ARIMA part 3
Intuition behind Integrating — ARIMA part 4
Building a ARIMA Model..
What is Normalization & How to normalize your data..
How to Featurize your Data.
Performing Dickey Fuller Test on Data
How to Hypertune your Time Series Model
Project 3–>> Predict the prices of Stocks
Dataset & resources
Collecting our Data for use-case
Perform Exploratory Data Analysis on data
Building Interactive Plots using Plotly
What is Co-relation & how to check your Features are co-related or not..
Perform Value at Risk analysis
Finding Relationship between your data
Analysing Historical Prices using Candle-stick
Prepare your data for Time Series Modelling..
Building & Intrepreting Facebook Prophet Model