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Course details

Learn 50 Hrs Hands on training on Artificial Intelligence Deep Learning , Optimization techniques from Industry experts.   We teach you the following course contents. 1. Python Packages like Keras, Theano, PyTorch.. 2. ANN, CNN, RNN, AutoEncoders, BackPropogation 3. Designing Neural and Deep learning algorithms on Image Classifications, Recognitions, Filtering Techniques 4. Application oriented training for working experts who wish to make their foot steps into AI/Advance Machine Learning Jobs.  

Course details

German Levels taught : Level : A1 Duration : 3 months Sessions per week : 4 Duration per session : 3 Hrs Fees per students : 9,500/- Level : A2 Duration : 3 months Sessions per week : 4 Duration per session : 3 Hrs Fees per students : 10,000/- Level : B1 Duration : 4 months Sessions per week : 4 Duration per session : 3 Hrs Fees per students : 15,000/- Level : B2 Duration : 6 months Sessions per week : 4 Duration per session : 3 Hrs Fees per students : 15,000/-

Course details

Duration : 50 Hrs

Length : 2 Months

Weekend : 3 Hrs per day ( Saturdays & Sundays )

Timings : 11AM till 2PM

Batch : 10 Students per Batch only

Venue : GotoMeeting link will be provided for the sessions.

Target Audience : Working Professionals, Job Seekers, PG/UG Students seeking internships 

Software Tool : R programming Language

Course Curriculum

• Refreshing concepts in fundamentals of Data Analysis, Statistical Analysis,
• Why learn R? How to install R Studio. familiarizing R software environment How to install R packages
• Basic computations in R, object classes and attributes, Data Types in R-vectors, matrices, lists and dataframes
• Control structures in R-IF-else,For, Loops

Data Preprocessing

• Data Input from various formats, Data Cleaning, Missing Data, Categorical Data, Coding, Dummy Variables, File merge, split, Data Manipulation
• Descriptive analysis, Exploratory Analysis
• Data Preparation
• Feature engineering
• Feature scaling
• Dimensionality reduction

Introduction to Artificial Intelligence and Machine Learning

• Artificial Intelligence Preview
• Machine Learning
• Machine Learning algorithms
• Applications of Machine Learning
• Techniques of Machine Learning
• Supervised Learning and Unsupervised Learning
• Some Important Considerations in Machine Learning

Supervised Learning – Regression,Regression and Its Types

• Linear Regression: Simple and Multiple Regressions, developing equations and algorithms,
• important metrics in regression, how to compute them and interpret results

Supervised Learning - Classification

• Classification Types:Logistic regression,K-nearest neighbours,Support Vector Machines,Kernel SVM,Naive Bayes,Decision tree classifier,Random forest classifier
• Comparing different classification type metrics and interpreting results.

Unsupervised learning - Clustering

• K-means Clustering
• Hierarchical Clustering
• Principal component analysis
• Extensive handson exercises on various datasets in Finance, Retail, Telecom & Banking

Course details

Title : Foundation for Data Analytics/Business Analytics/ Data Science Pre-requisite : Intention to learn and grab a good job opportunity Duration : 50 Hrs  Timings : 7.30 AM till 8:30 AM Days : Monday to Friday Instructurs : Working professionals in MNC and Financial Sector Students Type: MBA/BBM/BCom/MCA/BCA/BE/BTech or working professionals who look for better jobs / career change/ career enhancement.