Data Science with Python & R

About Course

At Affluenz IT Academy, our students often ask what’s the best programming language they should use for their day-to-day data analysis tasks. Our answer is that it depends on the type of data analytical challenge that they want to address.

Both Python and R, are popular programming languages for statistics.  While R has strong data visualization capabilities, Python is often praised for its easy-to-understand syntax. The best way to understand its usage is to work on various practical simulations and address them with R or Python.

We at Affluenz IT Academy build the base of our trainers with both the programming languages and provide me real time use cases to evaluate which one they need to adapt to address each of them

Key Features

  • 40 – 80 hours of instructor led online training
  • Certificate of completion
  • 2 Real-life Industry Project
  • Certificate of Internship
  • Virtual Internship
  • Dedicated awareness session from Industry experts

Online Classroom with virtual Internship

  • 3 Weeks’ course
  • 1 Week Live Project Internship
  • Certificate of completion
  • Certficate of Internship

9999/-

Online Classroom with Corporate Internship

  • 6 Weeks course
  • 2 Weeks Live Project Internship
  • Certificate of completion
  • Certficate of Internship

14999/-

Corporate Training

  • Self paced + Instructor Led classes
  • Flexible Pricing option

Why Data Science using Python & R?

According to Forbes, the cognitive and AI systems market will achieve an impressive 37.3% compound annual growth rate (CAGR) from 2017-2022. According to New IDC Spending Guide, IDC Worldwide Spending on Cognitive and Artificial Intelligence Systems Forecast to reach $77.6 Billion in 2022. According to a survey of 2,000+ data scientists and ML developers – conducted by Developer Economics in 2017 – Python takes the prize for being the most popular programming language for machine learning. Python also has a huge number of libraries that are ready to use for ML and data analysis purposes. R has a strong Data visualization capability and has the largest forum who provides both technical and functional support to its communities. If one has both Python and R programming language insights, she/he can master in depth Data Science concept

Who should take this Data science using Python & R Training course?

Affluenz IT Academy crafts this course to all who aspire to build a career in Data science & Machine learning like AI Engineer, Business Analyst, Information architect and so on. We recommend this course to:

  • Developers aspiring to be a data scientist or AI engineer
  • Analytics managers who are leading a team of analysts 
  • Business analysts who want to understand Predictive Analysis techniques
  • Information architects who want to gain expertise in Artificial Intelligence usage 
  • Analytics professionals who want to work in machine learning or artificial intelligence
  • Graduates looking to build a career in data science and machine learning
  • Experienced professionals who would like to harness Artificial Intelligence in their fields to get more insights

Pre-requisites of Data science using Python & R Course

Participants in this online course should have:

  • Basics of statistics and mathematics
  • Basic Data science concepts

4 Weeks Course

  1. Module 1: Basics of Data Science
    • What is Data Science
    • Data mining, optimization & Statistics
    • Learning Algorithms
  1. Module 2: R programming Basics
    • What is R
    • Journey of R
    • Programming basics & Syntax
  1. Module 3: Programming with R – R Studio
    • R Studio Essentials – Set up & Basic overview
    • Manipulate Package, Strings, regular and irregular time series management using RStudio IDE
  1. Module 4: Python Environment Setup and Essentials
    • What is Python
    • Journey of Python
    • Python (NumPy) – Mathematical Computing
    • Python (SciPy) – Scientific Computing
  1. Module 5: Python Vs R
    • When to use Python
    • When to use R
    • Key differences
  1. Module 6: Live Project on Python & R
  2. Assessment
  3. Live Project
  1. Module 7: Certification & Closure
    • Certification of Completion

8 Weeks Course

  1. Module 1: Basics of Data Science
    • What is Data Science
    • Data mining, optimization & Statistics
    • Learning Algorithms
  1. Module 2: R programming Basics
    • What is R
    • Journey of R
    • Programming basics & Syntax
  1. Module 3: Programming with R – R Studio
    • R Studio Essentials – Set up & Basic overview
    • Manipulate Package, Strings, regular and irregular time series management using RStudio IDE
  1. Module 5: Data Visualization and Machine Learning
    • What is Data Visualization
    • What is Machine Learning and how it is responsible for Data Visualization
  1. Module 5: Python Environment Setup and Essentials
    • What is Python
    • Journey of Python
    • Python (NumPy) – Mathematical Computing
    • Python (SciPy) – Scientific Computing
    • Data Manipulation with Pandas
  1. Module 6: Advanced Python
    • Natural Language Processing with Scikit Learn
    • Data visualization in Python using matpolib
    • Web scrapping
  1. Module 7: Python Vs R
    • When to use Python
    • When to use R
    • Key differences
  1. Module 8: Live Project on Python & R
  2. Assessment
  3. Live Project
  1. Module 9: Certification & Closure
    • Certification of Completion
    • Internship Certificate

Sample Certification

  • Certificate of Completion
  • Internship Certificate

Your Future Starts Here.