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Data Analysis with Python and Pandas

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120 STUDENTS
Overview Python is a popular programming language and Python developers are in demand these days. Data analysis is a skill …

Overview

Python is a popular programming language and Python developers are in demand these days. Data analysis is a skill that will boost your employability. Data Analysis with Python and Pandas course is designed for learners who have an interest in data analysis and familiarity with the programming language that they are ready to begin. The course will take learners through the basics of Panda before moving onto the more complex functions such as creating and navigating data frames.

It is a step by step approach and learners gain an in-depth understanding of data analysis, and using Python to manipulate your data. Learning data analysis will give learners a much in-demand skill that they can put to practical use in any business in the world.  If you’ve spent time learning Microsoft Excel and want to advance in your data analysis skills, this course is perfect for you.

Python is a widely used programming language, and will give learners an in-depth understanding of dozens of datasets and learners will realise how easy it is to get started with the course. Data Analysis with Python and Pandas will enable learners to take their Python programming and data analysis skills to the next level.

  • Why consider learning at Study 365?
  • Learning Outcomes
  • Access Duration
  • Who is this Course aimed at?
  • Entry Requirement
  • Method of Assessment
  • Certification & Awarding Body
  • Tutor Info
  • Progression and Career Path
  • Other Benefits

With so many commitments in our lives, we may not have the time to learn new skills. The beauty of studying online is that you get to find this balance between your education and your daily commitments

Study 365 offers hundreds of online courses to students across the world. Gaining new skills has never been this easy as many of our courses are open to students with little or no qualifications or previous experience. All the courses are up-to-date, relevant, affordable, and will build on existing expertise or give you a jump-start to a new career. The courses are meticulously designed and equals what is offered in a classroom setting. With a solid reputation that has established and made us made us one of the most trusted and reliable online course providers we offer the most convenient path to gain recognised skills and training that will give you the opportunity to put into practice your knowledge and expertise in your chosen career. You can learn at your own pace at Study 365 and you will be provided with all the necessary material, tutorials, qualified course instructor, narrated e-learning modules, interactive quizzes and free resources which include Free CV writing pack, free career support and course demo to make your learning experience enriching and more rewarding.

  • Learn efficient python data analysis
  • Manipulate data sets quickly and easily
  • Master python data mining
  • Gain a skill set in Python that can be used for various other applications
  • Python data analytics made simple

The course will be directly delivered to you, and you have 12 months access to the online learning platform from the date you joined the course.  The course is self-paced and you can complete it in stages, revisiting the lectures at any time.

  • This course is ideal for Data Analysts and Business Analysts
  • Python developers
  • Anyone who wants to learn Python programming
  • Basic experience in Microsoft Excel like Pivot Tables for example
  • Basic experience in Python programming

At the end of the course, you will have one assignment to be submitted (you need a mark of 65% to pass) and you can submit the assignment at any time. You will only need to pay £19 for assessment and certification when you submit the assignment. You will receive the results within 72 hours of submittal, and will be sent a certificate in 7-14 days if you have successfully passed.

Those who successfully complete the course will be awarded the Data Analysis with Python and Pandas certificate by CPD & iAP. The qualification will make you valuable to employers, and your motivation at gaining new skills will be recognised.

Harrison Kinsley is a husband, runner, friend of all dogs, programmer, teacher, and entrepreneur.

Harrison utilized his love for learning and building with technology to start multiple businesses, all of which leverage the Python programming language. Python and programming is a major part of his life and work. He believes programming is a super power, and the social impact of making this education easily accessible to anyone is one of the most important things he can do with his life.

Once you successfully complete the Data Analysis with Python and Pandas you will gain an accredited qualification that will give your career the jumpstart you have always wanted. With this qualification you can further expand your education or go onto work in numerous positions that will also put you in line to demand a higher salary or job promotion. The average UK salary per annum according to https://www.payscale.com/career-path-planner is given below.

  • .Net Programmer - £30,875 per annum
  • Web Developer - £24,833 per annum
  • Data Analyst - £25,511 per annum
  • Business Analyst - £35,543 per annum
  • Computer Programmer - £30,400 per annum
  • Software Engineer - £32,516 per annum
  • Software Developer - £24,833 per annum
  • Written and designed by the industry’s finest expert instructors with over 15 years of experience
  • Repeat and rewind all your lectures and enjoy a personalised learning experience
  • Gain access to quality video tutorials
  • Unlimited 12 months access from anywhere, anytime
  • Save time and money on travel
  • Learn at your convenience and leisure
  • Eligible for TOTUM discount card

Course Curriculum

1: Introduction To The Course
1.1 Course Introduction
1.2 Getting Pandas and Fundamentals
1.3 Section Conclusion
2: Introduction To Pandas
2.1 Section introduction
2.2 Creating and Navigating a Dataframe
2.3 Slices, head and tail
2.4 Indexing
2.5 Visualizing The Data
2.6 Converting To Python List Or Pandas Series
2.7 Section Conclusion
3: Io Tools
3.1 Section introduction
3.2 Read Csv And To Csv
3.3 io operations
3.4 Read_hdf and to_hdf
3.5 Read Json And To Json
3.6 Read Pickle And To Pickle
3.7 Section Conclusion
4: Pandas Operations
4.1 Section introduction
4.2 Column Manipulation (Operatings on columns, creating new ones)
4.3 Column and Dataframe logical categorization
4.4 Statistical Functions Against Data
4.5 Moving and rolling statistics
4.6 Rolling apply
4.7 Section Outro
5: Handling For Missing Data / Outliers
5.1 Section Intro
5.2 drop na
5.3 Filling Forward And Backward Na
5.4 detecting outliers
5.5 Section Conclusion
6: Combining Dataframes
6.1 Section Introduction
6.2 Concatenation
6.3 Appending data frames
6.4 Merging dataframes
6.5 Joining dataframes
6.6 Section Conclusion
7: Advanced Operations
7.1 Section Introduction
7.2 Basic Sorting
7.3 Sorting by multiple rules
7.4 Resampling basics time and how (mean, sum etc)
7.5 Resampling to ohlc
7.6 Correlation and Covariance Part 1
7.7 Correlation and Covariance Part 2
7.8 Mapping custom functions
7.9 Graphing percent change of income groups
7.10 Buffering basics
7.11 Buffering Into And Out Of Hdf5
7.12 Section Conclusion
8: Working With Databases 
8.1 Section Introduction
8.2 Writing to reading from database into a data frame
8.3 Resampling data and preparing graph
8.4 Finishing Manipulation And Graph
8.5 Section and course Conclusion

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