Data Science with Python Certification Training Course - PowerPoint PPT Presentation

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Data Science with Python Certification Training Course

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Data Science with Python certification course for Freshers & Working Professionals. Become a Data Scientist in 3 Months | 50 Hrs of Blended Learning | 6 Industry Projects | Placement Assured Program – PowerPoint PPT presentation

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Title: Data Science with Python Certification Training Course


1
Data Science Course With Python Machine Learning
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2
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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3
Data Science Course Syllabus
Machine Learning with Python
  • 1Introduction to Python Programming Language
  • Introduction and Installation of Python software
    Python packages Pandas, Numpy
  • Concepts of Data frame Filtering
  • Loc and iloc for filtering Usage of Boolean in
    Filtering Appending
  • 3 More data handling using Python
  • Pivot Table of Excel in Python Grouping function
  • Learning of SQL queries using Python Grouping
    numeric data
  • 4 Additional functions of Python
  • Text functions
  • Data cleaning with efficient text functions
    Inbuilt String functions of Python Reshape
    functions of Python
  • 2 Data handling in Python
  • Handling of Missing values If else statement
  • Extra trick of using if else statement Removal
    of Duplicates
  • Frequency Distribution
  • Merging Inner, Outer, Left and Right Binding
    and Appending
  • Descriptive Statistics
  • Inbuilt Numeric functions of R
  • 5 Statistic
  • Everything you want to know about
    statistics.Well sort of!! Mean, Median, Mode
  • Standard Deviation, Variance, Normal
    Distribution Hypothesis testing
  • T-test, Anova, Normality test

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4
  • 6 Linear Regression
  • Predictive Analytics Linear Regression
    Concepts of Linear Regression
  • Simple and Multiple Linear Regression Automatic
    Dummy Variables creation technique Model
    Validation parameters
  • Model Assumption testing
  • Splitting of data for Validation and testing
  • Business Case Study with real data to model in
    Python
  • 8 Logistic Regression
  • Predictive Analytics Logistic Regression
    Concepts of Logistic Regression
  • Difference between Linear Regression and
    Logistic Regression Automatic Dummy Variables
    creation technique
  • Model Validation parameters Model Assumption
    testing
  • Splitting of data for Validation and testing
  • Business Case Study with real data to model in
    Python
  • 7 Linear Regression Practice Case Study
  • Participants will be asked to develop a Linear
    Regression model on a real life data, in presence
    of the instructor. Time given is 2.5 hours.
    Participants will be treated like an industry
    employee, but in terms of help certainly the
    instructor will not be as ruthless as the boss.
    After completion of the model (with the help of
    the instructor wherever it is required), the
    instructor will show how to present a model to a
    real life client.

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5
  • 10Time Series Forecasting
  • Time series forecasting ARIMA
  • Difference between forecasting and prediction
    Concepts of time series data
  • Concepts of ARIMA
  • Descriptive analytics for ARIMA Development of
    model
  • Best model selection Forecasting with the best
    model Residual analysis
  • Business Case Study with real data to model in R
    software
  • Participants will be asked to develop a model in
    presence of the instructor.
  • 11 Cluster Analysis
  • Unsupervised Machine Learning with R Cluster
    Analysis Concepts
  • Cluster analysis with R K Means, Hierarchical
    etc.
  • 12 Decision Tree and Random Forest
  • Concepts of Decision Tree Decision Tree with
    Python Concepts of Random Forest Random Forest
    with Python

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6
Salary expectation after completing Data Science
course
  • As there is a growing demand for Data Science
    Engineers, the salary is also constantly
    increasing for Data Science skills,
  • As per payscale.com Average salary for Data
    Scientist is Rs 9,12,453 Per year.

Career after Data Science course
  • Large number of IT companies spread across World,
    you should not have any doubt on shortage of Data
    Science jobs. IT technologies is growing and
    there a huge demand for Data Science engineers.
    Data Science has more than 70 of the markets
    share in terms of providing services.

www.apponix.com
7
Office Address of Apponix Technologies
  • Head Office - Bangalore
  • 306, 10th Main, 46th Cross, 4th Block
    Rajajinagar, Bangalore - 560010
  • M 91 8050580888
  • info_at_apponix.com

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8
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