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Master Data Science with Python - From Zero to Master

Learn Python from scratch, quickly and effectively with our online course. Develop technical skills to become a highly qualified programmer in the job market and create your first program.

By Ivan Pinar Dominguez | Master in Project Management from ESDEN Business School,

👥 9.113
(26)
$15.99 USD $95.00

15 day refund guarantee

This course includes:

▪️ 6h 1m duration on demand

▪️ 86 lessons

▪️ 8 downloadable resources

▪️ Available on mobile devices

▪️ Access forever

▪️ Language:

  • Spanish

▪️ Unlimited consultations

✦ Bonus: Set of Downloadable Guides and Work Files

⚑ Certificate of completion

What you will learn

🟧 You will learn to master the general-purpose Python language from scratch, including its installation.

🟧 You will understand and delve into the complete flow of a Data Science project to become a data scientist.

🟧 You will learn all the statistical concepts necessary to be able to analyze the data around you.

🟧 You will use libraries such as Numpy or Pandas for importing from heterogeneous sources (CSV, Excel, plain text, SQL, Web, social networks, cloud,...) and data cleaning and transformation.

🟧 You will create powerful visualizations with the Matplotlib and Seaborn libraries for data analysis.

🟧 ​ You will analyze time series and make forecasts.

🟧 You will automate your daily tasks with Python.

🟧 ​You will acquire extensive knowledge in Data Science that you can apply immediately at a very affordable price compared to other programs.

Course content
U1: Introduction to Data Science with Python
  • Introduction to Python for Data Analysis
  • Setting up Python and Jupyter
  • Loading libraries and data sources
  • Basic graphics with Matplotlib
  • Practical exercise: Basic graphics with Matplotlib
  • Flowchart in a Data Science project
U2: Python Fundamentals from Scratch
  • Handling variables in Python
  • Lists: creation, extraction and modification
  • Advanced techniques for creating lists
  • Using built-in functions in Python
  • How to Create Functions and Use Flexible Arguments in Python
  • Using Lambda Functions
  • Methods in programming with Python
  • Creating dictionaries in Python
  • Creating dictionaries with the zip function
  • Using Comparators in Python
  • Loop structures in Python
  • List Comprehension in Python
U3: Basic Statistics for Data Analysis
  • Fundamentals of variables and basic concepts
  • Calculating the variance of a variable
  • ​Analysis of the correlation of variables
  • Creating and analyzing histograms
  • Studying data with percentiles
  • Calculation of probability density functions
  • Forecasting and Calculation of Moving Averages
U4: Numpy for numerical computation
  • Numpy Library Basics
  • Selecting data using arrays in Numpy
  • Working with 2D arrays in Numpy
  • Statistical operations with Numpy
U5: Pandas for Data Analysis
  • Pandas Fundamentals: Introduction to Dataframes
  • Generating dataframes from dictionaries
  • Import data from plain text files
  • ​Data selection techniques in Pandas dataframes
  • Useful tools for dataframes in Pandas
  • Data cleaning in data frames: duplicates and errors
  • Data interpolation techniques
  • Applying filters to Pandas dataframes
  • Sorting data in a dataframe
  • Add columns with text strings in dataframes
  • Generating columns in dataframes using maps and dictionaries
  • Using lambda functions to create columns in dataframes
  • Creating conditional columns in dataframes
  • Modifying column names and order in dataframes
  • Creating Pivot Tables with Pandas
  • Grouping data with groupby in Pandas
  • Union of dataframes by concatenation
  • Combining dataframes using merge
U6: Import and Export with Pandas
  • Importing data from Excel files
  • Fundamentals of relational databases and data models
  • Importing data from SQL databases
  • Extracting data from a web page
  • Web scraping techniques to import web data
  • Importing data from JSON files
  • Data extraction from social networks
  • Loading data from Cloud platforms (AWS, Azure, Google)
  • Exporting data to CSV and Excel files
  • Exporting data to SQL databases
U7: Data Visualization in Python - Matplotlib Library
  • Recommendations for data visualization
  • Matplotlib Basics
  • How to create line, bar and scatter charts
  • Advanced Chart Customization
  • How to Create Box and Whisker Plots
  • Generation of histograms and cumulative distribution functions
  • Creating Charts with Moving Averages
  • Using Subplots for Multiple Charts
  • How to apply styles to charts
  • Charts using groupby objects
  • Generation of two-dimensional histograms
  • Geographic maps with basemap
U8: Data Visualization in Python - Seaborn Library
  • Seaborn Library Basics
  • Linear regression with Seaborn
  • Creating stripplots with Seaborn
  • Creating swarmplots with Seaborn
  • Creating violinplots with Seaborn
  • Creating jointplots with Seaborn
  • Creating pairplots with Seaborn
  • Visualizing correlations with heatmaps
U9: Using Time Series in Python
  • Extraction and analysis of time series
  • ​Time series filtering
  • Resampling techniques in time series
  • Interpolation of data in time series
  • How to visualize time series
  • Generating forecasts using historical data
U10: Expanding the use of Python with other platforms
  • Task automation with Python scripts
  • Python in BI tools like Power BI
U11: Conclusions
  • Conclusions
Course evaluation
  • This course contains a final exam
G-Tools: For Students
  • Exclusive access to cutting-edge student tools: improve your employability, participate in exclusive events, take advantage of our intelligent virtual assistant, and more.
⚑ Certificate of completion
  • Your personalized digital certificate, a unique badge of your achievements, with international validity, course duration and QR code for instant verification.
__
Downloadable resources:

Downloadable Files.

*Password.
* Data Science with Python from Scratch_IPD.
* Master Data Science Python Datasets.
* Note 2.7 Python Methods.
* Note 6.8 Links to Cloud.txt libraries
* Note 9.8_corr method on non-numeric columns.
* Note 10.6 ARIMA library change.

Description

Do you want to start your journey to become a data scientist and master the field of Data Science?

If you're looking for a way to take your data analysis skills to the next level, this course is for you. Designed for both beginners and professionals who want to delve deeper into the world of data science, this course will guide you step-by-step through all the essential tools and techniques you need to become a data analysis expert.

In this program you will learn the complete fundamentals of Data Science, its statistical basis and how to put it into practice with Python, mastering this language from scratch, as well as all its powerful libraries such as Numpy, Pandas, Matplotlib or Seaborn focused on data analysis.

At the end of the course you will be able to execute complete Data Science projects, being able to import heterogeneous data sources, perform data cleaning and transformation, statistically analyze and visualize the information and obtain conclusions that have a high impact on your environment.

Why Choose This Course?

Practical and Applied Content: Each module includes practical exercises that will allow you to apply what you have learned in real-life situations.
Access to Exclusive Resources: Get access to datasets, Jupyter notebooks, and code examples that will help you consolidate your knowledge.

Constant Updates: We keep our content up to date with the latest trends and tools in data science.

Don't miss the opportunity to acquire skills that are in high demand in the job market. Apply today and take the first step towards a successful career in data science.

Act now! Start your journey to data science mastery with Python.

Your future as a data expert starts here!

Companies from all industries invest in the development of their teams with this course from G-Talent and Ivan Pinar Dominguez

Pack de 3 cursos

Ivan Pinar Dominguez

Master in Project Management from ESDEN Business School,

About Ivan Pinar Dominguez

Master in Project Management from ESDEN Business School,

The Passion and Experience You Need to Master Machine Learning

Ivan Pinar is a leading telecommunications engineer originally from Spain with an insatiable passion for technology, project management, and teaching. His dynamic and engaging approach to instruction ensures that each student gains the maximum value in knowledge for every minute invested in his classes.

With vast experience in the telecommunications industry, Ivan stays at the forefront of the latest technologies and trends. His ability to break down complex concepts into clear and concise explanations makes him an ideal instructor for students of all levels, from beginners to advanced.

What makes Ivan different?

Top-Level Technical Expertise: Ivan has worked on numerous innovative projects, acquiring deep practical and theoretical knowledge in advanced technologies. His industry experience allows him to offer real-world examples and practical applications that enrich his students’ learning.

Master in Project Management: Beyond his technical expertise, Ivan is an expert in project management. He has successfully led complex and multifaceted projects, imparting to his students the best practices and essential principles to manage projects effectively in any environment.

Student-Centered Approach: Ivan firmly believes that everyone has the potential to learn and achieve their goals. His student-centered teaching method creates a positive and motivating environment, where students feel comfortable to ask questions, experiment, and explore new ideas.

Passion for Teaching: Ivan’s dedication to education is palpable in every class he teaches. His enthusiasm and commitment ensure that each student not only learns, but is also inspired to continue developing and reaching new horizons.

If you are looking for an instructor who combines passion, experience and a deep commitment to your success, Iván Pinar is the perfect choice. Join his classes and discover how you can transform your knowledge and skills into real tools for success in the world of technology and project management.

Sign up now and learn from one of the best!

Discover the added value: G-Tools and much more

In addition to high-quality content, this course gives you access to G-Tools, a suite of tools and resources designed to enhance your learning and your career.

Employability support resources, live events and take advantage of Aixa.IA's artificial intelligence to resolve your questions at any time.

Customer Reviews

Based on 26 reviews
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(26)
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J
Jesús Manuel Martín Blanco
Recomiendo G-Talent cien por cien

Enseñanzas claras, precisas y de fácil entendimiento.

R
Rolando Muñoz Vargas
Excelente capacitación

Un curso muy completo y muy bien explicado.

J
Juan Carlos
Breve y sencillo

Muy buen curso y sobre todo bien preparado por el profesor. Propone retos en forma de ejercicios para que el alumno ejercite los conceptos en cada capitulo. Me compraré un par de cursos más de este profesor. Gracias.

J
Juan Carlos
Breve y sencillo

Muy buen curso y sobre todo bien preparado por el profesor. Propone retos en forma de ejercicios para que el alumno ejercite los conceptos en cada capitulo. Me compraré un par de cursos más de este profesor. Gracias.

J
Juan Carlos
Breve y sencillo

Muy buen curso y sobre todo bien preparado por el profesor. Propone retos en forma de ejercicios para que el alumno ejercite los conceptos en cada capitulo. Me compraré un par de cursos más de este profesor. Gracias.

L
Leyna Soranlly
Me gusto mucho la forma de enseñanza

Realmente el profesor explica muy bien, el curso está muy bien extructurado, me siento muy feliz de haber comprado el curso.

L
Leyna Soranlly
Me gusto mucho la forma de enseñanza

Realmente el profesor explica muy bien, el curso está muy bien extructurado, me siento muy feliz de haber comprado el curso.

L
Leyna Soranlly
Me gusto mucho la forma de enseñanza

Realmente el profesor explica muy bien, el curso está muy bien extructurado, me siento muy feliz de haber comprado el curso.

A
Ana Carina M.
Muy bien explicado

Me parece muy claro y fácil de entender, sobre todo para estudiantes que no dominan python y la ciencia de datos

A
Ana Carina M.
Muy bien explicado

Me parece muy claro y fácil de entender, sobre todo para estudiantes que no dominan python y la ciencia de datos

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