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"Data Science & Analytics, Machine Learning with Python" is no longer available

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Basheer Bagh, Hyderabad

Course ID: 46002

Basheer Bagh, Hyderabad

No Reviews Yet

About the Course

Data Science is no longer just a buzzword. Researchers at Forrester have "found that, in 2016, almost 40 percent of firms are implementing and expanding big data technology adoption. Another 30 percent are planning to adopt big data in the next 12 months." Similarly, the Big Data Executive Survey 2016 from NewVantage Partners found that 62.5 percent of firms now have at least one big data project in production, and only 5.4 percent of organizations have no big data initiatives planned or underway.

Why should you invest in this program?

Forbes and IBM in a research have given some inputs::
â?¢ The number of data science professionals in US alone would be around 700,000 by 2020
â?¢ This is expected to grow at an average rate of 28% year on year
â?¢ The average income for a Data Scientist is projected to reach USD 145,000 by 2020 from the current average of USD 90,000 in 2018.
â?¢ Worldwide requirement for Data Science and Analytics professionals is forecasted to be 4 million by 2020.
â?¢ At the current rate of learning and readiness world will still have a shortage in demand by 30% till 2025.


Are you right for this program (Audience)?

â?¢ Ideal for all graduates
â?¢ B.A, B.Com, B.Sc, B.E, B.Tech, M.Tech, MCA What will you learn?

The Data Science program has been designed to equip you with technology skills that are most desired by IT industry today.

The curriculum of this course covers concepts:
â?¢ Cloudera Hadoop
â?¢ Scala
â?¢ Apache Spark
â?¢ Core Python with PySpark
â?¢ Machine Learning With Python

Features of the program:

â?¢ Complete hands-on and practical oriented.
â?¢ Apart from classroom practical, students will get to work on project and prototype to create their own ML algorithm.
â?¢ We will help you setup the software on your laptop from the scratch for practice.
â?¢ Course will be taught by a single professional trainer with good expertise on the topic. Unlike many places where multiple trainers are involved.
â?¢ Processed flow of the program in scheduled and disciplined manner.
â?¢ Free video courses on Java, Oracle, and Introduction to Machine Learning, AI, Cloud, and Personal Development worth Rs. 20,000 along with the course.
â?¢ Live access to video courses and other reading material, white papers, research data through our learning portal for the next 1 year after course completion.

Course Details ILT Duration: 144 Hours

Cloudera Hadoop - 24 Hours
â?¢ Intro. Big Data & Hadoop
â?¢ Apache Hadoop
â?¢ Apache Hadoop Ecosystem
â?¢ Hadoop Core Components
â?¢ Hadoop Storage: HDFS
â?¢ Hadoop Processing
â?¢ MapReduce Framework
â?¢ Clouderaâ??s Distribution Hadoop
â?¢ CDH Architecture
â?¢ Hadoop Architecture and HDFS
â?¢ HDFS Deployments: (HA) & Non-HA
â?¢ HDFS (HA) Using (QJM)
â?¢ Data Replication Rack-Awareness
â?¢ HDFS Commands
â?¢ HDFS Administration Commands
â?¢ Hadoop MapReduce Framework
â?¢ MapReduce Architecture
â?¢ MapReduce Application Workflow
â?¢ Data Locality Optimization in Hadoop
â?¢ Resource Management Using YARN
â?¢ YARN (MRv2) Architecture
â?¢ Hive Arch. & Components
â?¢ Deep Dive in Hive
â?¢ Apache Sqoop , Sqoop Syntax
â?¢ Cloudera Impala
â?¢ Impala with Hive, HDFS, HBase Scala - 24 Hours
â?¢ Functional Programing Paradigm
â?¢ Introduction to Scala
â?¢ Data Types and Control Structures
â?¢ Collections
â?¢ Functional Programming using Scala
â?¢ Object Oriented Programming
â?¢ Singletons and traits
â?¢ Scala Indepth
â?¢ Advanced Scala concepts
â?¢ Extractors, Annotations & Parsing

Apache Spark - 16 Hours:
â?¢ Introduction to Big Data and Spark
â?¢ Foundation to Spark
â?¢ Working with Resilient Distributed DataSets (RDD)
â?¢ Spark Eco-system - Spark Streaming & Spark SQL

Core Python - 40 Hours:
â?¢ Installing Python
â?¢ Introduction
â?¢ The Basics of Python
â?¢ Program Flow Control in Python
â?¢ Lists,Ranges & Tuples in Python
â?¢ The Binary number system
â?¢ Python Dictionaries and Sets
â?¢ Input and output (I/O) in Python
â?¢ Modules and Functions in Python
â?¢ Object Oriented Python
â?¢ Using Databases in Python
â?¢ Generators, Comprehensions and Lambda Expressions
â?¢ Packages
â?¢ Introduction to PySpark

Machine Learning With Python â?? 40 Hours:
â?¢ Introduction of Data Science and Machine Leaning
â?¢ Introduction Python
â?¢ Data Structure & Data Manipulation in Python
â?¢ Statistics for Machine Learning
â?¢ Simple Linear Regression
â?¢ Multiple Linear Regression
â?¢ Polynomial Regression
â?¢ Support Vector Regression (SVR)
â?¢ Decision Tree Regression
â?¢ Random Forest Regression
â?¢ Logistic Regression
â?¢ K-Nearest Neighbors (K-NN)
â?¢ Support Vector Machine (SVM)
â?¢ Naive Bayes
â?¢ Decision Tree Classification
â?¢ Random Forest Classification
â?¢ K-Means , Hierarchical Clustering
â?¢ Deep Learning
â?¢ Apriori
â?¢ Upper Confidence Bound (UCB)
â?¢ Thompson Sampling
â?¢ Natural Language Processing
â?¢ Artificial Neural Networks

*Note: Can be taken individually, subject to meeting respective prerequisites.


Date and Time

Not decided yet.

About the Trainer

5 Avg Rating

3 Reviews

6 Students

7 Courses


BTech Oracle Certified Sun Certified

She is a senior consultant and trainer with more than 10 years of experience. She has been a senior practitioner and consultant on Databases, BigData, Data Science and has been involved with many assignments with large multinational companies. She has trainer more than 10000 students and corporate employees.

Her technology expertise is in Oracle, MySQL, Teradata, Hbase, Big Data Hadoop Ecosystem, Apache Spark, Scala, Kafka and Java.


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