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Training Courses

Data Analytics Using Python and R

  • Introduction to Python/R for Data Analysis
  • Python/R iteration, conditional constructs, libraries, data structures, using and defining functions, manipulating objects, and the exploratory analysis in Python/R
  • Introduction to Data Analytics, series and data frames, importing data from other file types, working with relational databases, using principal component analysis to simplify data, simplifying data with decomposition
  • Building a Predictive model in Python/R
  • Complete application based on data analytics
  • Application based on Predictive data analytics

Software Development and Testing

Big Data Using Hadoop

  • Introduction, Why Hadoop?, Its Core Components
  • The Hadoop Distributed File System
    (HDFS), Its features, writing and reading files, NameNode memory considerations, Overview of HDFS security, Web UIs for HDFS, Using the Hadoop file shell
  • MapReduce and Spark on YARN
  • Hadoop cluster installation
  • Getting data into HDFS
  • Installing and configuring Hive, Impala
  • Hadoop clients including Hue
  • Introduction to Pig and processing complex data with Pig, Multi-Dataset operations
  • Querying with Hive and Impala
  • Aggregating Data with Pair RDDs
  • Writing and Running Apache Spark Applications
  • Parallel Processing in Apache Spark
  • Message Processing with Apache Kafka

Web Development Using Php, Js, CSS, HTML

  • Training modules for learning different aspects of building a website from scratch
  • Frontend and Backend development
  • Introduction to HTML5, CSS3, JavaScript
  • Advanced Styling with Responsive Design
  • Building an E-commerce website

Machine Learning and AI

  • Introduction to AI & Python revision
  • Data processing and feature engineering using Numpy, Pandas, Matplotlib and Seaborn
  • Machine Learning primer with examples of popular ML algos (Regression & Classification)
  • Regression: Multinomial, Dimensionality Reduction: PCA, Decision Trees, Random Forest, Bayesian Classifiers, K-Means Clustering
  • Introduction to Deep Learning & its applications, Implications of deep learning on mobility, Foundation Algorithm – Introduction to Neural Networks
  • ANN with hidden layers, Activation function options, Linear versus non-linear functions, Building a multilayer neural network from scratch, Available libraries to work with (TensorFlow, Keras, TFLearn etc.)

Training Courses on Different Programming Languages

Training modules for different programming languages such as C, C++, Java, Python, Perl, .Net, Matlab etc.