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Bundle Combo - Data Science (with Python and R)

Self-paced videos, Lifetime access, Study material, Certification prep, Technical support, Course Completion Certificate



£26 inc VAT
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70 hours · Self-paced
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Lifetime access
No formal qualification
  • Uplatz Certificate of Completion - Free

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Uplatz provides this comprehensive bundle course on Data Science with Python and R. It is a self-paced course with recorded video lectures. You will be awarded Course Completion Certificate at the end of the course.

R is a powerful programming language that is widely used for statistical computing and data analysis. The evolution of the r language from a simple text editor to an interactive r studio. Only because of the generous contributions of r users around the world was this possible. R has become more powerful as a result of the addition of powerful packages. Data manipulation, computation, and visualization are now much faster thanks to packages like the data table. If you want to learn what r is in data science or what it means in data science, keep reading this article to learn more about it.

Python has become one of the most popular programming languages in the world in recent years. It's used in everything from machine learning to building websites and software testing. It can be used by developers and non-developers alike. Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed. Python is a powerful general-purpose programming language. It is used in web development, data science, creating software prototypes, and so on. Fortunately for beginners, Python has simple easy-to-use syntax. This makes Python an excellent language to learn to program for beginners. Python, one of the most popular programming languages in the world, has created everything from Netflix’s recommendation algorithm to the software that controls self-driving cars. Python is a general-purpose language, which means it’s designed to be used in a range of applications, including data science, software and web development, automation, and generally getting stuff done.

This Bundle Combo - Data Science (with Python and R) course teaches how to use R to solve real-world problems with a real-world dataset. It covers R's and Python’s functions and data types, as well as vector operations and advanced sorting algorithms. You'll learn how to manipulate, analyze, and visualize data, as well as how to use general programming tools like the "if-else" conditional construct and "for loop" commands. There are several programming assignments to help you remember what you've learned.

Students learn the fundamentals of R programming and Python Programming in Uplatz's Data Science with R and Python professional certificate program. Because there are no prerequisites for this course, it is suitable for anyone who is just starting out in the field of data science. It's also great for anyone who knows how to program in another language but wants to learn R.

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the NumPy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and Data Frame as the central data structures for data analysis, along with tutorials on how to use functions such as group by, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.


Uplatz Certificate of Completion

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1) Data Science with Python

Data science takes into account the whole process starting from understanding the business requirements to preparing the data for model building and deploying the insights finally. The whole process is handled by different professionals including Data Analysts, Data Engineers, and Data Scientists. The role depends upon the size of the company, sometimes all the processes are done by just one professional. Let us try to understand why python is the right programming language for Data Science. Python for Data Science is a must-learn skill for professionals in the Data Analytics domain. With the growth in the IT industry, there is a booming demand for skilled Data Scientists and Python has evolved as the most preferred programming language for data-driven development. Through this course, you will learn the basics, how to analyze data, and then create some beautiful visualizations using Python.

2) Data Science with R

R is a powerful language used widely for data analysis and statistical computing. It was developed in the early 90s. Since then, endless efforts have been made to improve R’s user interface. The journey of R language from a rudimentary text editor to interactive R Studio and has engaged many data science communities across the world. This was possible only because of generous contributions by R users globally. Inclusion of powerful packages in R has made it more and more powerful with time. Packages such as dplyr, tidyr, readr, data.table, SparkR, ggplot2 have made data manipulation, visualization and computation much faster. In these data science courses, you’ll learn how to use the R language to access databases, clean, analyze, and visualize data with R. This is an action-packed learning path for data science enthusiasts who want to work with real world problems using R.

Important Points to remember

  • Lay a solid foundation before moving on to more advanced courses.
  • Learn how to use R to perform confusion matrix analysis, model evaluation, data transformation, cross validation, and data exploration.
  • Discover how to use R to perform tasks like sorting and plotting.
  • Work with real-world data to develop problem-solving skills.

The Data Science with R programming and Python certification training covers data exploration, data visualization, predictive analytics, and descriptive analytics approaches using the R programming language. The following topics will be covered: R packages, data import and export, data structures in R, statistical principles, cluster analysis, and forecasting.

Course Objectives

  • Navigate and optimise the R integrated development environment (IDE) RStudio
  • Install and load add-in packages
  • Import external data into R for data processing and statistical analysis
  • Learn the main R data structures – vector and data frame
  • Compute basic summary statistics
  • Produce data visualizations with the g plot package
  • Solve fundamental error problems
  • Understand techniques such as lambdas and manipulating csv files
  • Describe common Python functionality and features used for data science
  • Query DataFrame structures for cleaning and processing
  • Explain distributions, sampling, and t-tests
  • Implement data science end-to-end with Python as well as R
  • Data Science use cases and build practical applications

Who is this course for?



Passion & determination to succeed!

Career path

  • Data Scientist
  • Machine Learning Engineer
  • Deep Learning Engineer
  • Python & R Programmer
  • Python Developer Data Science
  • R Developer Data Science
  • Software Developer
  • Solution Architect
  • Data Analyst
  • Cloud Engineer
  • Data Science Developer
  • Data Science Manager

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