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CAT1(FOUNDATION)-PREREQUISITes TO PURSUE DATA SCIENCE,ML & AI
All of our training courses in data science, actuarial science, python programming require a solid base on the following courses
Python Data Types, List Manipulation, Strings, Dictionaries,Tuples,Functions,Sets,Program Control Flow, Modules, Simulation
Comprehension (Multiple and Nested)Extended Keyword Arguments (*args, **kwargs)Closures and Decorators, Generators and Iterators Protocol@staticmethod & @classmethod Inheritance and Object Oriented Programming. Encapsulation, Operator Overloading. Python Packages and Program layout etc
Fundamentals of Mathematical Statistics & Probability, Descriptive Statistics, Discrete & Continuous Random Variables, Transformations, Distributions, Normal Distribution, Moment Generating Functions, Central limit theorem, Statistical Inference, Estimation Methods, Maximum Likelihood Estimation, Confidence Intervals, Hypotheses Test,Correlation,Regression Analysis,ANOVA, Credibility Theory,Byesian Networks, Mortality Estimation etc
Introduction to R and R Studio, Data structures: vectors, matrices, lists and data frames, Reading data into R from various data sources, Simple descriptive stats,Loops,Conditional expressions etc Merging data across data sources, Statistical modeling functions: lm and glm, Iterating with R. Logic and flow control, Simulation, Bootstrapping and Monte-Carlo simulation in R , Graphics , histogram,ggplot2,Dynamic and web reporting: Knitr and Shiny.
CAT2-ADVANCED STATISTICS & PROGRAMMING LANGUAGES FOR DATA SCIENCE,ML & AI
Statistical tools, and the programming languages are the backbone when we need to represent, model, manipulate & think about large quantities of data.
R programming language, developed by Ross is widely used for applications related to data science. R provides support for an extensive suite of statistical methods, inference techniques, machine learning algorithms, statistics, time series analysis, data analytics, graphical plots to list a few. These features make it a great language for data exploration and investigation.
Python programming has various frameworks & features to expand in , graphical user interfaces ,data analysis,web development data visualization etc. Python is extensively used by many organizations for various purposes in the field of data science.
Main topics are Numpy,Pandas,Seaborn,Matplotlib,Scipy and their applications actuarial science
Statistics, Estimation Methods, Confidence Interval, Hypotheses Test,Regression Analysis, Time Series Models & Applications,,ARIMA Model,Monte Carlo simulation, Generalized linear models, Bayesian Network Analysis, Markov Process, Stochastic Process,Bootstrapping,Hidden Markov Chains,Couplas,Extreme Value Theory, Multivariate Calculus etc.
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CAT3-STATISTICAL METHODS,DATA ANALYTICS & MACHINE LEARNING
The digital revolution has created vast quantities of data. Extracting knowledge and insight from this avalanche of information is the goal of data science, a rapidly growing field with applications in such areas as marketing, education, and sports, as well as scientific fields such as genomics, neuroscience, and particle physics in addition to statistics. Working with large data sets, they will build mathematical models, use advanced statistical methods & implement machine learning algorithms
Statistical data analysis are immensely useful in solving economic problems such as wages, price, time series analysis, demand analysis. We can use the skills in areas of work in Insurance, mortality, marketing, public health, biology, even sports.
Employment of statisticians is projected to grow 31 percent from 2018 to 2028, much faster than the average for all occupations. Growth is expected to result from more widespread use of statistical analysis to make informed business, healthcare etc.
Data science profoundly influences everything from business decisions to national security to what consumer products we buy. It impacts retail markets, solves public health dilemmas,Improves our manufacturing process to produce a better product.
We can better predict future disease outbreaks using the real-time exchange of clinical health information. A recent study on hiring trends in India indicates that 97,000 positions related to data science are currently vacant due to a dearth of skills.
Machine learning brings together computer science and statistics to harness that predictive power. It's a must-have skill for all aspiring data analysts and data scientists, or anyone else who wants to wrestle all that raw data into refined trends and predictions.
Machine Learning can be a rewarding career for students who are good in mathematics and statistics and have programming skills. The field of Machine Learning offers a promising career path with lucrative salaries.
CAT4-ARTIFICIAL INTELLIGENCE ,DEEP LEARNING & COMBO COURSES
AI is going to change the world more than anything in the history of mankind.Artificial Intelligence helps in finding solutions to complex business problems in a more human-like fashion..AI is applied on intelligent implementations, which includes robots, smart cars, consumer electronics etc. along with various apps and business solutions. A 2019 report from Gartner shows that enterprise applications for AI have grown 270% in four years, fueling a level of demand that outstrips the supply.
Course Covers In depth- R Programming, Python Programming, Advanced Applied Statistical Techniques.
Main Topics are Linear Regression, Logistic Regression, K nearest neighbors and Decision Trees, Support Vector machine, Random Forest, and Naive Bayes.
Dimensionality Reduction, k-means Clustering,Hidden Markov Model,DBSCAN Clustering, Principal Component Analysis, Singular Value Decomposition, Association Rule
Course Covers In depth- R Programming, Python Programming, Advanced Applied Statistical Techniques.
Main Topics are Linear Regression, Logistic Regression, K nearest neighbors and Decision Trees, Support Vector machine, Random Forest, and Naive Bayes. Dimensionality Reduction, k-means Clustering,Hidden Markov Model,DBSCAN Clustering,Principal Component Analysis,Singular Value Decomposition,Association Rule
Master the concepts of Deep Learning to build artificial neural networks,concept of NLP
The applicability of AI in a multitude of industries including entertainment, transportation, finance, retail etc. makes this technology a hot job & career destination. AI and machine learning have the potential to create an additional $2.6 trillion in value for marketing & sales by 2020.
Course Covers Machine Learning,Deep Learning,NLP,Fuzzy Logic, Image Classification, Computer Vision ,Logic Programming. Heuristic Search Techniques & Creating Intelligent Agents with Reinforcement Learning.
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