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About the course
Key Highlights
- Designed for Working Professionals
- 250+ Hours of Recorded Video Tutorials
- 15+ In-class & Capstone projects
- Live Classes- 5 days in a week & one day doubt clearing session
- Career assistance videos
- Placement Assistance (Job Opportunities Portal, Hiring Drives, Resume Building & more)
- EMI Option Available
- Post Graduate Program Certification from IIBM Institute along with Internship Certificate
- Course Duration: 6 Months
- Eligibility: Any Bachelors degree with 50% or equivalent at graduation, No minimum work experience required
CURRICULUM HIGHLIGHTS
Python Intro,IDE and Python Packages
Python Programming
Python Data Types – Dictionary, List and Set
Numpy Packages – Array Handling and Manupulation
Pandas Packages – Dataframe and Loading Excel, CSV File
Matplotlib Packages – Line graph and Visualisation
Histogram, Scatter Diagram, Box Plot and Bar Graph
Area Chart, Dual Axis, Array reshaping, reverse matrix analysis
Python – Operators and String Manupulation Control Structures(IF,IF-ELSE,IF-ELIF-ELSE,WHILE & FOR LOOP)
Python – Data Preparation Process
Python – Functions WITH and WITHOUT arguments
Python – File Processing and Data Collection Methods
Python – Time Series Analysis and Forcasting
Python – Simple Predictive Analysis
Data Science with Python
Data Science Application across Multiple Domain and Business Function
Data Science Project LifeCycle
Multiple Predictive Model using Python
Python – Simple and Multiple Predictive Model in Practical
Python Correlation Analysis
Python Classi cation Model Buildin
Data Science – Experimental Design Analysis
Classi cation Technique – Discriminant Analyssi
Data Science – Association Rule – Apriori Algorithm
Data Science – Building Recommendation System – (Market Basket Analysis) Data Architecture Design, Data Warehousing and it’s Schema Design Image Processing and Image Extraction Image Processing and Object Recognition Summarisation of Data Science Algorithm (Data Science Process)
Python Intro,IDE and Python Packages
Python Programming
Python Data Types – Dictionary, List and Set
Numpy Packages – Array Handling and Manupulation
Pandas Packages – Dataframe and Loading Excel, CSV File
Matplotlib Packages – Line graph and Visualisation
Histogram, Scatter Diagram, Box Plot and Bar Graph
Area Chart, Dual Axis, Array reshaping, reverse matrix analysis
Python – Operators and String Manupulation Control Structures(IF,IF-ELSE,IF-ELIF-ELSE,WHILE & FOR LOOP)
Python – Data Preparation Process
Python – Functions WITH and WITHOUT arguments
Python – File Processing and Data Collection Methods
Python – Time Series Analysis and Forcasting
Python – Simple Predictive Analysis
Data Science with Python
Data Science Application across Multiple Domain and Business Function
Data Science Project LifeCycle
Multiple Predictive Model using Python
Python – Simple and Multiple Predictive Model in Practical
Python Correlation Analysis
Python Classi cation Model Buildin
Data Science – Experimental Design Analysis
Classi cation Technique – Discriminant Analyssi
Data Science – Association Rule – Apriori Algorithm
Data Science – Building Recommendation System – (Market Basket Analysis) Data Architecture Design, Data Warehousing and it’s Schema Design Image Processing and Image Extraction Image Processing and Object Recognition Summarisation of Data Science Algorithm (Data Science Process)
Deep Learning Fundamentals
Working of Neural Networks
Gradient Descent and Back Propagation
Activation Function
Tensorflow Introduction
Building Artificial Neural Networks (ANN)
Deep Learning-ANN-classification
Computer-Vision-opencv-part1-overview
Computer-Vision-opencv-part2-face_detection
intro to CNN
Introduction to RNN & Sequence prediction using RNN
Introduction to LSTM,
Sequence prediction using LSTM
Applications in text analytics , stock prediction , time series data
Basics of NLP
Removing Stop Words
Stemming & lemmatization
Parts of speech tagging
TFIDF vectorizer
Senmiment Analysis
Text Classification with Linear Models
Language Modelling with Probabilistic Graphical Models and Neural Networks
Word Embeddings and Topic Models
Machine Translation and Sequence-To-Sequence Models
Model-Based Reinforcement Learning (Dynamic Programming)
Model-Free Reinforcement Learning (SARSA, Monte Carlo, Q-Learning)
Approximate and Deep Reinforcement Learning (Deep Q-Learning)
Policy Gradient Reinforcement Learning
Advanced Topics on Exploration and Planning
Tableau introduction
Different types of visualization using Tableau
Tableau Dashboard Creation
Tableau Story line creation
Time series using Tableau
Different types of Joins Using Tableau
Tableau Features – Filters and format the Column
Real time project using Tableau
Tableau Highlighter
Data Blending using Tableau
Table Calculation using Tableau
Parameters and Set using Tableau
Advanced Data Preparation using Tableau
Hierarchical clustering using Tableau
Complete Course Revision using Tableau
What is R? And Why R?-Different “flavors” of R-Installing R Studio DesktopUnderstanding R Studio-Installing Packages and Libraries in R Studio-Setting Your Work Directory.
Data Variables-Data Types – Operators – Keywords – ExceptionsFunctions
Vectors and Lists – Strings and Matrices – Arrays and Factors – Data Frames – Packages.
R- CSV files Read and Write and analyze the data – R- Excel files Read and Write and analyze the data
Introduction to Visualisation – Line Plots and Bar Charts – Pie Chart and Histogram – Scatter Plots and Parallel Coordinates – Advanced Plotting – Exporting Plots and Other Plotting Packages
Linear Regression Analysis – Formulation of Regression Model – Bivariate Regression – Statistics Associated with Bivariate Regression Analysis – Conducting Bivariate Regression Analysis – Multiple Regressions – Conducting Multiple Regression – Mapping Bivariate Regression with Real Time Example.
Logistic Function – Single Predictor Model – Determine Logistic Cut off – Estimated Equation for Logistic Regression
Factor Analysis Introduction – Factor Analysis Model – Statistics associated with Factor Analysis – Conducting Factor Analysis – Construction of Factor Analysis – Factor Analysis Method – Principal Component Analysis – Rotation Method – Mapping Factor Analysis with Real Time Example
Cluster Analysis Introduction – Statistics associated with Cluster Analysis – Conducting Cluster Analysis – Classification of Clustering Procedure – Hierarchical Clustering – Non Hierarchical Clustering
Association Rule Introduction – Apriori Algorithm – Multiple Association Rules – Market Basket Analysis (MBA) – Application of Apriori Algorithm and Market Basket Analysis
Naïve Bayes Introduction – Probabilistic Basics and Probabilistic Classification – Characteristics of Naïve Bayes – Real Time Case study using Naïve Bayes – Advantage and Shortcoming of Naïve Bayes
K – Nearest Neighbour Introduction – K – Nearest Neighbour Algorithm – Pre-Processing your dataset for KNN – How to measure “Nearby” – Choosing “K” and High “K” vs. Low “K” – Real Time case study using KNN – Advantage and Disadvantage of KNN
What is a Decision Tree? – How to create Decision Tree – Choosing and Identifying attributes for Decision Tree – Entropy and Information Gain with Intuitions – Pruning Trees and its types – Forward Pruning and Backward Pruning – Sub tree Replacement and Raising – Real time case study with Decision Tree
Ensample of Decision Tree.
Linear SVM using Hyperplane – Non-Linear Hyperplane using Kernal Trick and Advantage and Disadvantage of SVM
RFM Segmentation and Analysis – Propensity Modelling and its application – Churn Modelling using Operational Analytics – Fundamentals and Modelling Framework – Industry application – Market Basket Analysis using Marketing Analytics – Fundamentals and Analysis Framework – Industry Application – Price and In store Promotion using Retail Analytics – Price Elasticity and Optimization – Promotion Effectives using Analytics
PROGRAMMING LANGUAGES AND TOOLS
Capstone Projects
Capstone Recorded Projects
Financial Analytics
Unsupervised Machine Learning – Merger and Acquisitions Analytics
Banking Analytics
Bank Loan Modeling – Automation of loan eligibility process – Dream Housing Finance Company
Gaming Analytics
Prediction of English Premier League (EPL) Championship
Supply Chain Analytics
Zomato Delivery Performance Analysis
HR Analytics
Employee Attrition Rate Analysis
Banking Analytics
Team Deposit Plan – Machine Learning Classification – Portuguese Bankinh Institution
Retail Analytics
Predicting house prices for using supervised Machine Learning
Real Estate Analytics
Predictive Analytics with model simulationm – Ames Housing Authority.
HR Analytics
Employee Termination Analysis
Customer Analytics
Principal Component Analysis – Dimension Reduction – LKP Share & Securities.
In-Class capston Projects
Financial Market Prediction
Analysis the Real-time Stock market using Regression
Diabetic Diagnostic Prediction
Predict the Medical condition of Person
Flower Species Classification
Iris Flower classification is done using sepal and petal
Titanic Survival
Will person survive on titanic ship .
Cancer Detection
Will classify the person detect with cancer or not Customer Segmentation : Customer will divided into segments and behavior will analyze
Loan Prediction
Person will be loan defaulters in future of not .
MNIST Digit Classification
kids Handwritten digits will be classified
Wine Quality Test
test the wine quality and classifiy it.
CERTIFICATION
WILL I GET CERTIFIED?
On completion of the Post Graduate Program Certification in Cloud Computing and Devops, aspirants will receive an Industry-endorsed Certificate along with Internship Certificate.
MENTORSHIP
Our Industry mentor team will guide you with:
– Provide unparalled 1:1 support and guidance
– Help execute in-class assignments and case studies
– Discuss & identify learning gaps and other solutions such as refresher sessions and one-on-one project feedback
-Set learning goals
-Discuss your progress status with trainers and other industry mentors on a regular basis to ensure consistent advancement
Dinesh
Babu R
Qualification: P.hd in Data Analysis, MBA (Finance & Operation), B.Tech
Abhishek Srivastava
Qualification: M.Tech (CS), MCA
Program Fees
Financing Option:
” IIBM Institute of Business Management” provides education loan through a Landbox.
For more details contact to loansolutions@iibminternships.com
