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GreaterHeight Technologies LLC ~ GreaterHeight Academy
  • All Courses
    • BI and Visualization
      • Mastering Data and Business Analytics
        • Basic Excel for Data Analysis
        • Intermediate and Advanced Excel for Data Analysis
        • Excel for Business Analysis & Analyst
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        • Data Analytics and Visualization with Tableau
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Data Analysis Using Python With Numpy & Pandas


GreaterHeight Academy designed this course to help you master two of the most popular Python packages for data analysis: NumPy and Pandas.


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Data Analysis Using Python With Numpy & Pandas 



Who this course is for:

  • Analysts or BI professionals looking to learn data analysis with NumPy and Pandas.
  • Aspiring data scientists who want to build or strengthen their Python skills.
  • Anyone interested in learning one of the most popular open source programming languages in the world.
  • Students looking to learn powerful, practical skills with hands-on projects and course demos.


What you will Learn:

  • Master the essentials of NumPy and Pandas, two of Python's most powerful data analysis packages.
  • Analyze and manipulate dates and times for time intelligence and time-series analysis.
  • Import and export flat files, Excel workbooks and SQL database tables using Pandas.
  • Learn how to explore, transform, aggregate and join NumPy arrays and Pandas DataFrames.
  • Visualize raw data using plot methods and common chart options like line charts, bar charts, scatter plots and histograms.
  • Build powerful, practical skills for modern analytics and business intelligence.

Course Benefits & Key Features

Data Analysis Using Python With Numpy and Pandas’ benefits and key features.
Modules

30+ Modules.

Lessons

80+ Lessons

Practical

40+ Hands-On Labs

Life Projects

5+ Projects

Resume

CV Preparations

Job

Jobs Reference

Recording

Session Recording

Interviews

Mock Interviews

Support

On Job Supports

Membership

Membership Access

Networks

Networking

Certification

Certificate of Completion


INSTRUCTOR-LED LIVE ONLINE CLASSES

Our learn-by-building-project method enables you to build

practical or coding experience that sticks. 95% of our                        

learners say they have confidence and remember more               

when they learn by building real world projects which is                

required to work in your real life.


  • Get step-by-step guidance to practice your skills without getting stuck
  • Validate your technical problem-solving skills in a real environment
  • Troubleshoot complex scenarios to practice what you learned
  • Develop production experience that translates into real-world
.

Python Data Analytics & Visualization Job Outlook


.

Ranked #1 Programming
Language

TIOBE and PYPL ranks Python as the most popular global programming language.

Python Salary
Trend

The average salary for a Python Developer is $114,489 per year in the United States.

44.8% Compound annual growth rate (CAGR)

The global python market size is expected to reach USD 100.6 million in 2030.



  • Python Developer
  • Data Analyst
  • Python Data Scientist

Job Titles include:


  • Data Scientist
  • AI Engineer


  • AI Researcher
  • Machine Learning Engineer


Python Tools Covered

.

Why Data Analysis Using Python With Numpy & Pandas?

Learn In-demand Skills

Those with careers in data analysis learn relevant in-demand skills that span industries and add value to every digital-enabled organization.


Earn a Higher Salary

Experienced data analysts can earn up to $112,000 per year and transition into higher-paying jobs as Senior Data Analysts, Data Scientists, or Analytics Managers.

Positive Job Outlook

The data analytics market is predicted to hit $132.90 Billion USD by 2026. COVID-19 pandemic accelerated the adoption of data analytics solutions and services.

Shape the Future

Data analysts transform organizations by capitalizing on data to improve their business decisions and solve critical real-world problems.

Become a Leader

Being a central part of an organization’s decision-making processes, analytics experts often pick up strong leadership skills as well.

Data Analysis are Constantly Evolving

Data analysis moves quickly, and data analysts are constantly learning and advancing in their careers.




GreaterHeight Certificates holders are prepared to work at companies like these.

Some Alumni Testimonies

Investing in the course "Become a Data Analyst" with GreaterHeight Academy is great value for the money and I highly recommend. The trainer is very knowledgeable, very engaging, provided us with quality training sessions on all courses and was easily acessible for queries. We also had access to the course materials and also the timely availability of the recorded videos made it easy and aided the learning process..

QUEEN OBIWULU

Team Lead, Customer Success

The training was fantastic, the instructor is an awesome lecturer, relentless and not tired in his delivery. He obviously enjoys teaching, it comes natural to him. We got more than we expected. He extended my knowledge of Excel beyond what I knew, and the courses were brilliantly delivered. They reach out, follow up, ask questions, and in fact the support has been great. They are highly recommended and I would definitely subscribe to other training programs from them.

BISOLA OGUNRO

Fraud Analytics Risk Oversight Manager

It's one thing to look for just a Data Analysis training, and it's another to get the knowledge transferred through certified professional trainers. No matter your initial level of proficiency in any of the Data Analysis tools, GreaterHeight Academy would meet you there and take you up to a highly proficienct and confident level in a short time at a reasonable pace. I learnt a lot of Data Analysis tools and skills at GreaterHeight from patient and resourceful teachers.

TUNDE MEREDITH

Operation Director - Abbfem Technology

The Data Analysis training program was one of the best I have attended. The way GreaterHeight took off with Excel and concluded the four courses with Excel was a mind blowing - it was WOW!! I concluded that I'm on the right path with the right mentor to take me from a novice to professional. GreaterHeight is the best as far as impacting Data Analysis knowledge is concern. I would shout it at the rooftop to recommend GreaterHeight to any trainee that really wants to learn.

JOHN OSI PETER

Greaterheight

I wanted to take a moment to express my deepest gratitude for the opportunity to study data analytics at GreaterHeight Academy. I am truly impressed by the level of dedication and support that the sponsor and CEO have put into this program. GreaterHeight Academy is without a doubt the best tech institution out there, providing top-notch education and resources for its students. One of the advantages of studying at GreaterHeight Academy is the access to the best tools and technologies in the field. 

AYODELE PAYNE

Sales/Data Analyst

It is an unforgettable experience that will surely stand the test of time learning to become a Data Analyst with GreaterHeights Academy. The Lecture delivery was so impactful and the Trainer is vast and well knowledgeable in using the applicable tools for the Sessions. Always ready to go extra mile with you. The supports you get during and after the lectures are top notch with materials and resources available to build your confidence on and off the job.

ADEBAYO OLADEJO

Customer Service Advisor (Special Operations)

Data Analysis Using Python With Numpy & Pandas Course

Master the essentials of Numpy and Pandas, two of Python's most powerful data analysis packages. Learn how to explore, transform, aggregate and join Numpy and Pandas DataFrames. Analyze and manipulate dates and times for time intelligence and time-series analysis. 


Visualize raw data using plot methods and common chart options like line charts, bar charts, scatter plots and histograms. Import and export flat files, Excel workbooks and SQL database tables using Pandas. Build powerful, practical skills for modern analytics and business intelligence. We'll start with a NumPy primer to introduce arrays and array properties, practice common operations like indexing, slicing, filtering and sorting, and explore important concepts like vectorization and broadcasting.


From there we'll dive into Pandas, and focus on the essential tools and methods to explore, analyze, aggregate and transform series and dataframes. You'll practice plotting dataframes with charts and graphs, manipulating time-series data, importing and exporting various file types, and combining dataframes using common join methods.

WEEK 4-6 | 9 Modules | 8+ Hours | 5+ Skills

Course Modules


  1. DOWNLOAD: Course Resources
  2. Introducing the Course Project
  3. Setting Expectations
  4. Jupyter Installation & Launch

  1. Pandas & NumPy Intro
  2. Numpy Arrays & Array Properties
  3. Array Creation
  4. Random Number Generation
  5. Indexing & Slicing Arrays
  6. Array Operations
  7. Filtering Arrays & Modifying Array Values
  8. Filtering & Modifying Arrays
  9. Array Aggregation
  10. Array Functions
  11. Sorting Arrays
  12. Aggregation & Sorting
  13. Vectorization
  14. Broadcasting
  15. Bringing it all together
  16. Key Takeaways

  1. Series Basics
  2. Pandas Data Types & Type Conversion
  3. The Series Index & Custom Indices
  4. The .loc Accessor
  5. Duplicate Index Values & Resetting The Index
  6. Accessing Data & Resetting The Index
  7. Filtering Series & Logical Tests
  8. Sorting Series
  9. Sorting & Filtering Series
  10. Numeric Series Operations
  11. Text Series Operations
  12. Series Operations
  13. Numerical Series Aggregation
  14. Categorical Series Aggregation
  15. Series Aggregation
  16. Missing Data Representation in Pandas
  17. Identifying Missing Data
  18. Fixing Missing Data
  19. Applying Custom Functions to Series
  20. Pandas Where (vs. NumPy Where)
  21. Apply & Where
  22. Key Takeaways

  1. DataFrame Basics
  2. Creating a DataFrame
  3. Exploring DataFrames: Heads, Tails & Sample
  4. DataFrame Basics
  5. Exploring DataFrames: Info & Describe
  6. Accessing DataFrame Columns
  7. Accessing DataFrame Data with .iloc & .loc
  8. Accessing DataFrame Data
  9. Dropping Columns & Rows
  10. Identifying & Dropping Duplicates
  11. Missing Data
  12. Filtering DataFrames
  13. The Query Method
  14. Sorting DataFrames
  15. Renaming & Reordering Columns
  16. Arithmetic & Boolean Column Creation
  17. Advanced Conditional Columns with Select
  18. The Select Function
  19. The Map Method
  20. Multiple Column Creation with Assign
  21. Map & Assign
  22. The Categorical Data Type
  23. Type Conversion
  24. Memory Usage & DataTypes
  25. Downcasting Numeric Data Types
  26. DataFrame DataTypes
  27. Key Takeways

  1. Basic Aggregations
  2. The Groupy Method
  3. Groupby
  4. Grouping By Multiple Columns
  5. Multi-Index DataFrames
  6. Modifying Multi-Indices
  7. Multi-Index DataFrames
  8. The Agg Method & Named Aggregations
  9. The Agg Method
  10. Transforming DataFrames
  11. Transforming a DataFrame
  12. Pivot Tables in Pandas
  13. Multiple Aggregation Pivot Tables
  14. Pivot Table Heatmaps
  15. Melting DataFrames
  16. Pivot & Melt
  17. Key Takeaways

  1. The matplotlib API & The .plot() Method
  2. Basic Line Chart
  3. Chart Titles
  4. Line Styles
  5. Chart Legends & Gridlines
  6. Chart Styles
  7. Stylized Line Chart
  8. Subplots & Figure Size
  9. Bar Charts
  10. Grouped & Stacked Bar Charts
  11. Pie Charts & Scatterplots
  12. Scatterplots
  13. Histograms
  14. Saving Plots & Further Exploration
  15. Key Takeaways

  1. Times in Python and Pandas
  2. Converting To Datetimes
  3. Formatting Dates
  4. Date & Time Parts
  5. Pandas Datetime Basics
  6. Time Deltas & Arithmetic
  7. Time Series Indices
  8. Missing Time Series Data
  9. Shifting Time Series
  10. Shift & Diff
  11. Aggregation & Resampling
  12. Resampling
  13. Rolling Aggregations
  14. Key Takeaways

  1. Preprocessing with read_csv
  2. Column Selection
  3. Row Selection & Missing Values
  4. Parsing Dates & Data Types
  5. Converters
  6. Importing Data
  7. Importing from Text & Excel Files
  8. Exporting to Flat Files
  9. Importing & Exporting Excel Data
  10. Working With SQL Databases
  11. Other Supported File Formats
  12. Key Takeaways

  1. Why Multiple Tables
  2. Appending DataFrames
  3. Joining DataFrames
  4. Join Types
  5. Inner Joins
  6. Left Joins
  7. The Join Method
  8. Key Takeaways

DATA ANALYTICS USING PYTHON WITH NUMPY & PANDAS COST


United States

$300.00

United Kingdom

£626.75

Nigeria

N1,222,000.00

Career and Certifications


GreaterHeight Academy's Certificate Holders also prepared work at companies like:



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FAQs

Data Analysis Using Python With Numpy & Pandas

  • Among the various programming languages available in the market, Python has made its way to become one of the fastest-growing languages. Python can be used for many applications like building web applications, game development, machine learning, scientific and numerical computing. Learning Python is beneficial whether you want to become a data scientist, machine learning engineer, data analyst, or even a software developer.

  • Python is one of the most widely used programming languages in present times. It is a versatile language with a rich set of libraries that are used in many application areas like data science, web development, game development, scientific computing, machine learning, and eCommerce. Our Python course can help you become proficient in using this in-demand language and succeed as a Python developer.

  • GreaterHeight Academy’s Python course is the first step beginners can take to gain expertise in this language without any difficulty. The course curriculum is designed by industry experts and all the concepts are explained thoroughly.

  • Certainly, Python is one of the fastest-growing programming languages and it is a highly-valued skill in today’s job market. Due to its applications in a wide range of fields, many companies across the world are seeking Python developers. Moreover, Python skills can help you achieve a job in machine learning, data science, web development, and other fields. Our Python certification can further improve your career prospects.

  • A Python developer is generally expected to design, build, deploy, and debug development projects, usually on the back-end. They write effective and scalable Python codes as per business needs to design and implement robust applications. Their other responsibilities vary according to the field they work in. Achieve Greaterheight Academy's Python certification to understand what it takes to become a successful Python developer.

  • Python developers should have a firm understanding of Python basics along with object-oriented programming concepts. According to the field of work, Python developers should be familiar with the related frameworks and libraries. They are also expected to have a good understanding of ORM libraries, front-end technologies, version control systems, and more. Our Python certification is one of the best ways to develop such skills.

  • Python programming is a must-have skill for many trending job roles like data scientist, software developer, machine learning engineer, business intelligence analyst, data engineer, and data analyst. Greaterheight Academy’s Python certification can help you become eligible for all these job roles.

  • When compared to other languages, Python has quite simple syntax and English-like commands, making it easier for learners to grasp its basics. Our Python certification is suitable for beginners and the concepts are explained step-by-step to help them build a strong foundation in Python.

  • Python language has a simple syntax and English-like commands which makes it easy to learn. However, to become a Python programmer, you need a higher level of expertise and understand how to use it in a variety of applications. This Python course can help you get hands-on experience in using Python and its powerful libraries that is required to become a Python programmer.

  • GreaterHeight Academy’s Python training is offered by highly qualified trainers who have years of proven experience in Python programming and have worked on various industry projects. They also have rich experience in training students and giving them the best learning environment.

  • This Python certification course is ideal for professionals willing to become software developers or preparing for any data-related role like data scientist, data analyst, or AI engineer.

GreaterHeight Academy provides instructor-led training sessions conducted via live video streaming. It is a platform where candidates can communicate with the trainers, get the knowledge and get their queries resolved. Moreover, recordings of each class are also given to the candidates for reference.

  • According to ZipRecruiter, the average annual salary of a Python Programmer in the United States is $115,066. By getting Python certified, such professionals can further increase their salary.

  • All our mentors are highly qualified and experience professionals. All have at least 8-10 yrs. of development experience in various technologies and are trained by GreaterHeight Academy to deliver interactive training to the participants.

  • Yes, we do. As the technology upgrades, we do update our content and provide your training on latest version of that technology.

All online training classes are recorded. You will get the recorded sessions so that you can watch the online classes when you want. Also, you can join other class to do your missing classes.

  • Yes, we do. We will discuss all possible technical interview questions and answers during the training program so that you can prepare yourself for interview.

  • No. Any abuse of copyright is taken seriously. Thanks for your understanding on this one.

  • Yes, we would be providing you with the certificate of completion of the program once you have successfully submitted all the assessment and it has been verified by our subject matter experts.

  • Yes. But you can also raise a ticket with the dedicated support team at any time. If your query does not get resolved through email, we can also arrange one-on-one sessions with our support team. However, our support is provided for a period of Twelve Weeks from the start date of your course.

  • GreaterHeight is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry ready. You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.

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