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 or ML leverage 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.
R is a dynamic language widely used for data analysis and statistical computing. R language was developed in the early 90s and has traveled from a fundamental text editor to an interactive R studio engaging many data science communities in the world.
Data scientists strive on making the data useful in many ways by applying their coding and statistical skills. The mastery of data visualization, data exploration, analytics techniques with R language will help implement real-life projects across industries.
A course that equips you with the tools of statistical thinking so essential for data science. A self-paced learning program that strengthens the core concepts, probability, and statistical machine learning, gives the data scientist an edge over the others.
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 by Mazenet covers advanced statistical and analytical techniques. Further, the course content will allow you to learn more about logistic regression, forecasting with time series data and decomposition, implementing ARIMA models, neural networks and survival analysis.
Data analytics plays a vital role in the digital lives of consumers, becomes 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.
Complete training on tree-based modeling from basics in R and Python is considered to be one of the best and often used supervised learning methods. The tree-based learning algorithms. Every analyst should equip himself with the decision tree method to empower predictive models with accuracy.
Aspiring professionals with any educational background including IT professionals, Analytics Managers, business analysts, banking and finance professionals, supply chain network managers, marketing managers, and beginners can also take data science training.
Mazenet’s data science training conducts holistic sessions that follow up with a continuous evaluation scheme. Learners are evaluated through case studies, quizzes, assignments, and project reports.
Mazenet’s experienced corporate trainers will deliver a content with a mix of interactive lectures. Additionally, the training session also comprises of live lectures or hangout sessions dedicated to solving all your academic queries and reinforced learning.