Predictive analytics is the branch of the advanced analytics which is used to make predictions about unknown future events. Predictive analytics uses many techniques from data mining, statistics, modelling, machine learning, and artificial intelligence to analyse current data to make predictions about future.
One class of Predictive Analytics is to make prediction on Time Series Data. Studying historical data, collected over a period of time, can help in building models using which future can be predicted. For example, from historical data on Temperatures in a City, we can make decent predictions of what the Temperature could be in a future date. Or for that matter, from data collected over a reasonably long period of time regarding various life style aspects of a Diabetic patient, we can predict what should be the volume of Insulin to inject on a given date in future. One example to consider from the Business world could be to predict the Volume of In-Roamers in a Telecom Network in any given period of time in the future from the historical details of In-Roamers in the Network.
The applications are just innumerable as these are applicable in every sphere of business and life.
In this course, we go through various aspects of building Predictive Analytics Models. We start with simple techniques and gradually study very advanced and contemporary techniques. We cover using Descriptive Statistics, Moving Averages, Regressions, Machine Learning and Neural Networks.
This course is a series of 3 parts.
In Part 1, we use Excel to make Numerical Predictions from Time Series Data.
We start by using Excel for 2 reasons.
Excel is easy use and thus we can understand complex concepts through exercises that are easy to replicate and thus become easy to understand.
Excel is expected to be available with everyone taking this course.
In Part 2, we use R Programming to make Numerical Predictions from Time Series Data.
In Part 3, we use Python Programming to make Numerical Predictions from Time Series Data.
The course uses simple data sets to explain the concepts and the theory aspects. As we go through the various techniques, we compare the various techniques. We also understand the circumstances where a particular technique should be applied. We will also use some publicly available data sets to apply the techniques that we will discuss in the course.
From time to time, we will add bonus videos of our real time work on industrial data on which we will apply the Predictive Analytics techniques to create Models for making predictions.
- Basic Knowledge of Statistics
- Basic Knowledge of Algebra
- Basic Knowledge of Logarithm
- Basic Knowledge of Excel
Who should take this course
- Research Scholars
- Developers curious about Data Sciences
- Learners curious about Predictive Analytics
Course Completion Certificate
What will you learn
- Predicting using Descriptive Statistics, Moving Averages, Centred Moving Averages, Weighted Moving Averages
- Predicting using Linear Regression
- Predicting using Exponential Regression
- Predicting using Power Regression
- Predicting using Logarithmic Regression
- Predicting using Polynomial Regression
- Using Excel to make Predictions
- Using Data Analysis Tool Pak from Excel
- Using LINEST(), LOGEST(), GROWTH(), TREND() functions in Excel
About Course Provider
Simpliv LLC, a platform for learning and teaching online courses. We basically focus on online learning which helps to learn business concepts, software technology to develop personal and professional goals through video library by recognized industry experts or trainers.
With the ever-evolving industry trends, there is a constant need of the professionally designed learning solutions that deliver key innovations on time and on a budget to achieve long-term success.
Simpliv understands the changing needs and allows the global learners to evaluate their technical abilities by aligning the learnings to key business objectives in order to fill the skills gaps that exist in the various business areas including IT, Marketing, Business Development, and much more.
How to enroll?
You can book the course instantly by paying on GulfTalent.