Time Series Analysis Real world use-cases in python

Time Series Analysis Real world use-cases in python

Time Series Analysis Real world use-cases in python

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

Language: english

Note: 4.3/5 (33 notes) 11,628 students

Instructor(s): Shan Singh

Last update: 2021-12-24

What you’ll 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



  • Basic Programming of Python is recommended..



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-on  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 , AI  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.

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 Bitcoin  : 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..


Who this course is for

  • One who is curious about Data Science, AI, Machine Learning, Natural Language Processing, Time Series Analysis..


Course content

  • Introduction
    • Intro to this course & course Benefits
    • Utilize QnA Section ( Golden Opportunity ) !
    • 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


Time Series Analysis Real world use-cases in pythonTime Series Analysis Real world use-cases in python

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