Predictive Modeling & Evaluation with Machine Learning
Data Science Course series Main Module connecting Big Data Analytics and Visualiszation and Statistical Concepts to create Predictive Models using Linear Regression with Machine Learning. Can be done with R or Python. Will empower you with the Data Science skills to start making accurate forecasts and estimations with the data you have in any functionality across any industry.[/ultimate_ctation]
All those who are on Data Science journey and have learnt programming language R or Python for Big Data Analytics and Visualisation as well as Statistical concepts and now wish to move on to creating Machine Learning Models for forecasting and Prediction. It provides the basis for all advanced ML and AI models development and implementation.[/ultimate_ctation]
This level of Ambeone’s Certification Data Science course in Dubai covers Predictive Modelling, Basic Machine Learning & AI with R and starts you on the Machine Learning and Artificial Intelligence.
Predictive Modeling is the core concept underlying Machine Learning.It is a very creative and rewarding field and it is is here to stay. Therefore, we have designed hands-on and practical curriculum for our course in Certification Training in Predictive Modeling and Basic Machine Learning with R for Managers, Decision Makers, Business Analysts and future Data Analysts and Data Scientists!
Developing Predictive Models using Big data Analytics is a fast evolving phenomenon just like the IT revolution was in the 90’s. Due to technological advancements, data is being generated digitally like never before. By applying statistical methods to this massive amounts of data or Big Data, data scientists are able to conduct data analysis to find trends, patterns, correlation & outliers in their business of interest. Consequently this translates to determining opportunities and risks ahead of time and taking data-driven business decisions using Predictive Modeling techniques that improve business efficiencies, increase profits, mitigate risks and even open up new markets.
The level builds on all concepts for data interpretation, data visualization and exploration, statistical analysis and uses them to create Predictive Modeling for different business applications using linear regression.
Participants need to successfully complete all earlier levels in our Data Science series for Data Analysis and statistical concepts and Knowledge/Skills in R or Python for big data analytics and visualization is a pre-requisite for this module level in our Data Science Training Series.
On completion of this level, participants will be able to conduct Big Data Analytics and develop Machine Learning Algorithms for Predictive Modeling based on linear Regression which will empower them to conduct incisive analytics for better and accurate business predictions and forecast related decisions in any functionality across any industry.
You will also learn to build, evaluate and Fit your models for forecasting based on any kind of data for any business challenge across any functionality or industry.
To help our participants, Ambeone offers a discounted Package covering all our initial levels in Data Science Series with this this level as a comprehensive program ‘Foundation program in Data Science’.
The course structure covers all our Data Science series levels related to Statistics and Big Data Analytics & Visualization all the way up to Predictive Modeling using basic Machine Learning algorithm with R Language.
Due to popular demand from outstation candidates and corporates, we also offer this program as 5- Day Intensive Boot Camp as Big Data Analytics, Predictive Modeling and Basic Machine Learning with R.
Due to popular demand from International candidates and corporates, we also offer this program as 5- Day Intensive Boot Camp as “Big Data Analytics, Predictive Modeling and Basic Machine Learning with R”.
The boot camp over five days is planned to enable the International students and corporate executives to quickly enter and start working in this fast growing Data Science field.
Basic knowledge in Data Analysis and statistical concepts is a pre-requisite for this course level in our Data Science Training Series and 5 Day bootcamp.
Please call on 04-4425320 for finding more about joining the next bootcamp.
Topics covered in Training Module on Predictive Modeling with Basic Machine Learning with R
- Correlation and Regression
- Linear Regression using Machine Learning Models
- Exploratory Data Analysis
- Simple and Multiple Regression case studies in R
- Model Evaluation Parameters
- Examination of Residuals Plots
- Homoscedasticity and other error patterns
- Multicollinearity and Variance Inflation Factor (VIF)
Once you have mastered topics covered in this level, you can do this level either based on R or Python as the base programming language for Big Data Analytics, Data Visualization and Machine Learning for regression based predictive modeling.
Our carefully planned and recommended learning structure for Data Science Series
|Fundamental of Data Analytics & Interpretation ,Simple Measures of Data
|Business Intelligence & KPI Measurement using Statistics
|Statistics for Data Analytics & Data Science
|Big Data Analytics & Visualization with R
|Advanced Data Mining & Manipulation with Python
|Predictive Modeling & Evaluation with Machine Learning
|Advance Machine Learning and Artificial Intelligence with R & Python
|Applied Analytics-Using Data Science & Machine Learning in Business Analytics
|Neural Network & Unsupervised Learning for Advanced AI
Ultimately Data is everywhere and being able to leverage it for business applications and it is a skill that is very much in demand for today’s world of Big Data!
16 hours of Instructor Led Sessions
15 hours of Assignments & Capstone Projects
Four Hours Sessions each Weekend for 4 weeks for Public batches
Five Days Intensive Bootcamps/Workshop for International/ Corporate batches
Participants in this course must have completed our course in Statistics. Or, they must demonstrate good understanding of Statistics by passing an examination prior to course registration. This course heavily relies on Statistical Theory to build Statistical & Big Data Analysis Models.
They should also have proficient skills in big data analytics and visualization using R or Python.
We offer Discount Packages for the prerequisite introductory courses needed to successfully complete this course. Contact our team to know more.
Big Data Analytics is an evolving science with new and unique applications cropping up every day. Check out our carefully planned and recommended sequence of training courses that will ensure you gain all the necessary skills needed in a systematic and meaningful way to succeed as a Data Scientist!
Course Details for Training in Big Data Analytics & Predictive Modeling with R
- This course is offered as ,
- 5 Day Intensive Boot-Camp: This format of training is conducted over 5 working days in the morning.
- Evening Classes. Two 2-hour sessions a week for six weeks in the evenings: This format of training is beneficial for the working executives so that they are able to attend after work hours.
- As part of our Six Month Associate in Big Data Analytics: Participants can join an on-going batch for the relevant modules.
- Participants must bring their own laptop. Preferably with more than 8GB ram.
- This Big Data Analytics Training Module will be mainly taught using R as the programming language. Participants are not required to have any programming background. While we will cover necessary topics in R needed for this course, participants interested to further explore programming in R can check out our detailed course on Programming in R.
- All softwares and Databases used for the course are open-source and participants will be taught how to install and set-up the environment.
- All training topics covered in the course will be taught using relevant industry specific case studies and examples.
- In addition to the above, the course is very hands-on/practical and is not a lecture or seminar. Participants will be expected to complete exercises and case studies on their own with necessary support and guidance from the instructor.