Data science with python

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Data Science with Python Certification Training
Course With Placement Assurance
This
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Data Science Course Objectives

• Python full coding from scratch
•  Visualization with Python
•  Statistics - theory and application in business
•  Machine Learning with Python - 6 different
  algorithms
•  Multiple Linear regression
•  Logistic regression
•  Variable Reduction Technique - Information Value
•  Forecasting - ARIMA
•  Cluster Analysis
•  Decision Tree
•  Random Forest
•  Case studies on Machine Learning (18 case
  studies)
•  SQL queries(with Python)
•  Business Presentation of Technical Solution
  in-front of end client.
•  Robotic Automation(with Python)
•  CV Building activities
•  Interview preparation
•  Mock Interview sessions

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Data Science Course Syllabus

• Machine Learning with Python
• R Programming
• Data Analytics with MS-excel

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R Programming

• 1 Introduction to R Programming Language
• 2 Data handling in R
• 3 More data handling using R
• 4 Additional functions of R

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Machine Learning with Python

• 1Introduction to Python Programming Language
• 2 Data handling in Python
• 3 More data handling using Python
• 4 Additional functions of Python
• 5 Statistic
• 6 Linear Regression
• 7 Linear Regression Practice Case Study
• 8 Logistic Regression
• 9 Logistic Regression Practice Case Study
• 10Time Series Forecasting
• 11 Cluster Analysis
• 12 Decision Tree and Random Forest

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Data Analytics with MS-excel

• 1 Introduction to Excel
• 2 Different Functionalities of MS Excel
• 3 Analytics with Excel
• 4 Advanced Analytics with Excel

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Data Science Job Responsibilities Modify
existing databases and database management
systems (DBMS) or instruct programmers and other
analysts to make essential changes. Write and
code logical and physical database descriptions
and specify identifiers of database to management
system or direct other colleagues in coding
descriptions. Review project requests
describing database user needs to estimate time
and cost required to accomplish project. Review
data results to ensure accuracy. Configure data
visualizations for stakeholders Provide data
analysis and standard reporting support, which
includes the ability to extract data from various
sources and data stores by executing light
business coding (SQL, VBA, Unix, etc.) and system
parameter setting, perform ad-hoc queries and
develop/automate financial/statistical models
using a variety of known software applications
and tools (Excel, Access, etc.) Support the use
of data science and machine learning within the
various PSE engineering DevOps teams.
Manipulate and analyze complex, high-volume,
high-dimensionality data from varying sources
using a variety of tools and data analysis
techniques Translates business requirements
throughout the development process, delivers
solutions in accordance with business strategies,
standards, and processes. Develop business
cases for RD initiatives, provides expert advice
to product managers, developers, architects and
business partners on data science use cases and
options. Architect highly scalable distributed
systems, using different open source tools.
Working with lambda architectures and batch and
real-time data streams. Understand high
performance algorithms and Python statistical
software and brief team.
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Contact Us M 91 9069980888  E-mail-
info_at_apponix.com

• Corporate Office  306, 10th Main, 46th Cross,
  4th Block Rajajinagar, Bangalore - 560010 

www.apponix.com
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www.apponix.com