Perform arithmetic operations and alignment through the best academic program and with the most disruptive methodology: Relearning"

Both NumPy and Pandas are essential in the field of Python programming, due to their versatility in data analysis. These tools provide mechanisms to efficiently import, clean, exploit, analyze and prepare data. In addition, these resources offer powerful tools for data cleaning, including detecting and addressing missing, duplicate or outlier values. In this way, computer scientists ensure data quality prior to analysis. Moreover, these libraries are easily integrated with other visualization libraries such as Seaborn to design graphs and other informative visualizations that help communicate the data.

In this context, TECH is launching a comprehensive program that will delve into data management in Python using NumPy and Pandas. The syllabus will delve into the creation and Manipulation of Arrays, to represent data in multiple dimensions.

Likewise, the syllabus will analyze in detail the Vectorized Operations, taking into account the universal functions and looking for maximum efficiency. On the other hand, the academic materials will address the advanced customization of graphics, exploring different styles and configurations. In addition, the program will provide students with state-of-the-art tools for advanced data analysis and effective visualizations. Graduates will be prepared to face real challenges in the field of data analysis and visualization.

Professionals have a unique opportunity to be up to date in this field through a university program that they can take whenever and wherever they want. All you need is a cell phone, Tablet or computer with an Internet connection to view, at any time of the day, the content hosted on the virtual platform. In this way, the students have an educational option that is compatible with their more demanding responsibilities.

You will master Vectorized Array Operations to perform efficient and elementary calculations on arrays instead of explicit loops"

This Postgraduate certificate in Tools in NumPy and Pandas contains the most complete and up-to-date program on the market. The most important features include:

• The development of practical cases presented by experts in Python Development
• The graphic, schematic and practical contents of the book provide theoretical and practical information on those disciplines that are essential for professional practice.
• Practical exercises where the self-assessment process can be carried out to improve learning
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• The availability of access to content from any fixed or portable device with an Internet connection.

Manage the Matplotlib library to create a wide variety of graphs and communicate trends in data"

The program’s teaching staff includes professionals from the sector who contribute their work experience to this program, as well as renowned specialists from leading societies and prestigious universities.

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations.

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year For this purpose, the students will be assisted by an innovative interactive video system created by renowned and experienced experts. 

Looking to handle incomplete data in Pandas? Detect all null values with this program in only 150 hours”

You will organize your time and pace of study, adjusted according to your schedule, through TECH's complete Virtual Campus"

With an eminently practical approach, this Postgraduate certificate will enable students to obtain advanced skills in data management using NumPy and Pandas. The academic itinerary will cover from basic operations with Arrays to the manipulation and transformation of these elements.  The syllabus will delve into various strategies for concatenation, data merging and the use of pivot tablet.

On the other hand, the didactic materials will analyze how to create and customize graphics, so that the graduates can integrate them with Pandas to achieve an effective visualization of information. In addition, the program will provide the most modern tools to perform advanced data analysis.

You will nurture your IT procedures with the most effective strategies for handling incomplete data"

Module 1.  Data Handling in Python with NumPy and Pandas

1.1. Creating and Manipulating Arrays in NumPy

1.1.1. NumPy
1.1.2. Basic Operations with Arrays
1.1.3. Arrays Manipulation and Transformation

1.2. Vectorized Operations with Arrays

1.2.1. Vectorization
1.2.2. Universal Functions (ufunc)
1.2.3. Efficiency and Performance

1.3. Indexing and Segmentation in NumPy

1.3.1. Access to Elements and Slicing
1.3.2. Advanced and Boolean Indexing
1.3.3. Reordering and Selection

1.4. Pandas Series and DataFrames

1.4.1. Pandas
1.4.2. Data Structures in Pandas
1.4.3. DataFrames Manipulation

1.5. Indexing and Selection in Pandas

1.5.1. Access to Data in Series and DataFrames
1.5.2. Selection and Filtering Methods
1.5.3. Use of loc e iloc

1.6. Operations with Pandas

1.6.1. Arithmetic Operations and Alignment
1.6.2. Aggregation and Statistics Functions
1.6.3. Transformations and Application of Functions

1.7. Handling Incomplete Data in Pandas

1.7.1. Detection and Handling of Null Values
1.7.2. Filling and Elimination of Incomplete Data
1.7.3. Strategies for Handling Incomplete Data

1.8. Strategies for Handling Incomplete Data

1.8.1. Concatenation and Data Merging
1.8.2. Grouping and Aggregation (groupby)
1.8.3. Pivot Tables and Crosstabs

1.9. Visualization with Matplotlib

1.9.1. Matplotlib
1.9.2. Graphics Creation and Customization
1.9.3. Integration with Pandas

1.10. Customizing Graphics in Matplotlib

1.10.1. Styles and Settings
1.10.2. Advanced Graphics (scatter, bar, etc.)
1.10.3. Creating Complex Visualizations

Delve into the most up-to-date academic content in the IT landscape, available in innovative multimedia formats to optimize your study. And it's all through TECH!"