Mazenet has a well-researched courseware covering basics in Data Management, Statistics and Analytics to advanced topics like Machine Learning, Neural Networks and Big Data. Corporate employees will walk out with an in-depth understanding of data science and how it influences various industries like telecom, e-commerce, transportation and others.

Python

Created by Guido van Rossum in the year 1992, Python is a programming language that enables you to effectively integrate your systems and work faster.

Machine Learning

Machine Learning or ML has contributed to practical speech recognition, self-driven cars, effective web search and a better understanding of the human genome. Machine Learning is part of artificial Intelligence where the science of making computers to act without being specifically programmed.

Data Analytics with R

R is a dynamic language widely used for data analysis and statistical computing. R language was developed in the early 90s and has travelled from a fundamental text editor to an interactive R studio engaging many data science communities in the world.

Data Science with R

Data scientists strive on making the data useful in many ways by applying their coding and statistical skills. The mastery on data visualization, data exploration, analytics techniques with R language will help implement real-life projects across industries.

Statistics Essentials for Analytics

A course that equips you with tools of statistical thinking so essential for data science. A self-paced learning program that strengthen the core concepts, probability and statistical machine learning, gives the data scientist an edge over the others.

SAS

SAS or otherwise known as “Statistical Analysis System” is a platform by the SAS Institute that enables easy accessibility of analytics for those who seek insights from data via a rich interface. Adapts to the complete range of analytics and data challenges faced, embracing the open source technology for consistency.

Advanced Predictive Modeling in R

Advanced predictive modelling in R by Mazenet covers advanced statistical and analytical techniques. Further the course content will allow you to learn more on logistic regression, forecasting with time series data and decomposition, implementing ARIMA models, neutral networks and survival analysis.

Analytics for Retail Banks

Data analytics plays a vital role in digital lives of the consumers, become a data-driven marketing expert by acquiring the knowledge of concepts around data infrastructure, analytical lifecycle, customer lifecycle and digital trends in retail banking across the globe.

Decision Tree Modeling

A complete training on tree based modelling from basics in R and Python, is considered to be one of the best and often used supervised learning method. The tree based learning algorithms. Every analyst should equip himself with decision tree method to empower predictive models with accuracy.