Data Science with Python Training in Madrid

SKU: 11074
12 Lesson
|
40 Hours
igmGuru is a renowned Data Science with Python training institute in Madrid. Our course content is curated by industry experts to help you learn Python from basic to advanced level. We have delivered this training to more than 500+ individuals. Enroll today and successfully become Data Scientist, Data Analyst, Data Engineer, and more.
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Data Science with Python Training in Madrid

Data Science with Python Course in Madrid Overview

Our course content includes all the important Python developer skills such as such as Operators, Control Flow Statements, Data types, Data Manipulation, and more. The increasing Python developer salary is one of the reasons we have covered all the important topics that are required to become a developer successfully. We at igmGuru also provide post training support such as interview preparation, job assistance program, etc.

Prerequisites

Here are the prerequisites for Data Science with Python science with python course:

  • Basic Python programming
  • Foundations in mathematics
  • Data handling skills
  • Use of Python tools
  • Logical thinking and problem-solving
  • Foundational Knowledge in Algorithms

What Will You Learn

In this program, you will learn Python along with below topics.

  • Data Science Overview
  • Data Analytics Overview
  • Statistical Analysis and Business Applications
  • Python: Environment Setup and Essentials
  • Mathematical Computing with Python (NumPy)
  • Scientific computing with Python (Scipy)
  • Data Manipulation with Python (Pandas)
  • Machine Learning with Python (Scikit-Learn)
  • Natural Language Processing with Scikit-Learn
  • Data Visualization in Python using Matplotlib
  • Data Science with Python Web Scraping
  • Python integration with Hadoop, MapReduce and Spark

Additionally, you can also explore our detailed guide on what is Data Science in Python and How to Become a Python Developer.

Key Features

Data Science With Python Training in Madrid Modules

1. Data Science
2. Data Scientists
3. Examples of Data Science
4. Python for Data Science
1. Introduction to Data Visualization
2. Processes in Data Science
3. Data Wrangling, Data Exploration, and Model Selection
4. Exploratory Data Analysis or EDA
5. Data Visualization
6. Plotting
7. Hypothesis Building and Testing
1. Introduction to Statistics
2. Statistical and Non-Statistical Analysis
3. Some Common Terms Used in Statistics
4. Data Distribution: Central Tendency, Percentiles, Dispersion
5. Histogram, Bell Curve, Hypothesis Testing
6. Chi-Square Test, Correlation Matrix, Inferential Statistics
1. Introduction to Anaconda
2. Installation of Anaconda Python Distribution - For Windows, Mac OS, and Linux
3. Jupyter Notebook Installation, Jupyter Notebook Introduction
4. Variable Assignment
5. Basic Data Types: Integer, Float, String, None, and Boolean; Typecasting
6. Creating, accessing, and slicing tuples
7. Creating, accessing, and slicing lists
8. Creating, viewing, accessing, and modifying dicts
9. Creating and using operations on sets
10. Basic Operators: 'in', '+', '*', Functions, Control Flow
1. NumPy Overview
2. Properties, Purpose, and Types of ndarray
3. Class and Attributes of ndarray Object
4. Basic Operations: Concept and Examples
5. Accessing Array Elements: Indexing, Slicing, Iteration, Indexing with Boolean Arrays
6. Copy and Views, Universal Functions (ufunc)
7. Shape Manipulation, Broadcasting, Linear Algebra
1. SciPy and its Characteristics, SciPy sub-packages
2. SciPy sub-packages –Integration, SciPy sub-packages – Optimize
3. Linear Algebra
4. SciPy sub-packages – Statistics, SciPy sub-packages – Weave
5. SciPy sub-packages - I O
1. Introduction to Pandas
2. Data Structures, Series, DataFrame, Missing Values
3. Data Operations, Data Standardization
4. Pandas File Read and Write Support
5. SQL Operation
1. Introduction to Machine Learning
2. Machine Learning Approach
3. How Supervised and Unsupervised Learning Models Work
4. Scikit-Learn
5. Supervised Learning Models - Linear Regression, Logistic Regression
6. K Nearest Neighbors (K-NN) Model
7. Unsupervised Learning Models: Clustering, Dimensionality Reduction
8. Pipeline, Model Persistence, Model Evaluation - Metric Functions
1. NLP Overview
2. NLP Approach for Text Data
3. NLP Environment Setup
4. NLP Sentence analysis, NLP Applications
5. Major NLP Libraries, Scikit-Learn Approach
6. Scikit - Learn Approach Built - in Modules, Scikit - Learn Approach Feature Extraction
7. Bag of Words, Extraction Considerations
8. Scikit - Learn Approach Model Training
9. Scikit - Learn Grid Search and Multiple Parameters
10. Pipeline
1. Introduction to Data Visualization
2. Python Libraries, Plots
3. Matplotlib Features: Line Properties Plot with (x, y), Controlling Line Patterns and Colors, Set Axis, Labels, and Legend Properties, Alpha and Annotation, Multiple Plots, Subplots
4. Types of Plots and Seaborn
1. Web Scraping
2. Common Data/Page Formats on The Web
3. The Parser, Importance of Objects
4. Understanding the Tree, Searching the Tree
5. Navigating options, Modifying the Tree
6. Parsing Only Part of the Document
7. Printing and Formatting, Encoding
1. Need for Integrating Python with Hadoop
2. Big Data Hadoop Architecture
3. MapReduce, Cloudera QuickStart VM Set Up
4. Apache Spark
5. Resilient Distributed Systems (RDD)
6. PySpark, Spark Tools
7. PySpark Integration with Jupyter Notebook
Talk To Us

We are happy to help you

1-800-7430-173 (US Toll Free)
+91 7240740740 (India)
Drop Us a Query
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Request For Live Demo Class

Course Fees

Online Class Room Program

US $ 599.00
100% Money Back Guarantee
  • Duration : 40 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 28 May 2026
  • Weekday Batch 01 Jun 2026
  • Weekend Batch 30 May 2026

Corporate Training

Corporate Training
  • Customized Training Delivery Model
  • Flexible Training Schedule Options
  • Industry Experienced Trainers
  • 24x7 Support
Contact Us

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Want to know Today's Offer

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Data Science with Python Certification Exam

Official certification exam name is Data Science with Python - Certified Associate (varies by provider)

Exam Format

  • Duration: 90 to 120 minutes
  • Number of Questions: 60–80
  • Passing Score: 65–70%
  • Type: Multiple-choice, multiple-response, and coding-based questions
  • Mode: Online (proctored) or in-person at certified centers

Exam Cost

  • Fee: $150 to $295 USD depending on certification provider

igmGuru provides a Course Completion Certificate for Data Science with Python Training. This certification validates your knowledge in Python for data analysis, visualization, and basic machine learning concepts. It also confirms your understanding of tools such as Pandas, NumPy, Matplotlib, and Scikit-learn used in data science projects. This certification can support roles such as Data Analyst, Junior Data Scientist, and Python Developer.

Data Science with Python Certification Exam

Python Online Training in Madrid FAQ

Yes, igmGuru offers several other online courses under Business Intelligence. These include specialized online courses, tailored to different skill levels. igmGuru greatly emphasizes upskilling and boosting career opportunities across IT industry sectors, with each online course designed to help learners enhance their expertise in Business Intelligence. Below are few courses.

Yes, igmGuru offers several other online certification courses. These include specialized online certification courses, tailored to different levels. igmGuru, greatly emphasizes upskilling and boosting career opportunities across any industry sectors, with each online certification course designed to help learners enhance their expertise.

Yes, IgmGuru delivers Data Science with Python Corporate Training in Madrid.
Contact Us
Contact Us Worldwide
1-800-7430-173
(US Toll Free)
+91-7240-740-740
(India)
WhatsApp
+91-7240-740-740
(WhatsApp)
info@igmguru.com

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