Jose Portilla
Jose Portilla is a Data Scientist, full stack developer and entrepreneur who has been designing, building and analysing data-driven systems for more than 15 years. In this Python for Data Science and Machine Learning Bootcamp, he will teach you about the fundamental concepts of data science with Python and machine learning with an emphasis on getting your started.
In the Python Bootcamp, we’ll help you understand and master the basics of Python programming. You’ll learn how to work with data structures like lists and tuples, write functions and methods, perform mathematical operations in Python, handle exceptions to guarantee code quality and more!
This is a hands-on course that will teach you the skills to use Python as a tool for data science and machine learning. Whether you’re new to programming or already have experience with other languages, DataCamp offers plenty of support. This course covers all the fundamentals of data science—from handling and cleaning data, to statistics and probability theory, to supervised and unsupervised learning methods.
Python for Data Science and Machine Learning Bootcamp
The Python for Data Science and Machine Learning Bootcamp is designed to help you gain the skills necessary to start your career in data analytics. In this bootcamp, we will teach you all about how to use Python as a tool for data analysis and machine learning.
Do you want to master the skills necessary to use Python for data science and machine learning?
Python
Python is the most important programming language to learn as it has a strong presence in the data science and machine learning community. Python is a general-purpose programming language that can be used for web development, scientific computing, data analysis and visualization. Once you are proficient in Python, you will have the ability to solve any problem within minutes compared to other competing languages like C++ or Java. This bootcamp prepares you to enter one of the fastest growing industries in America by teaching you how to work with big data, complex algorithms, use data mining and machine learning techniques that are used by companies like Facebook, LinkedIn or Google.
This bootcamp has been designed for Python developers who want to understand the fundamentals of Machine Learning and avoid investment in complex techniques. This course offers a hands-on learning experience covering the basics of NumPy, Pandas, Graphistry, matplotlib, Scikit-learn and pandas’s dataframe.
This is a Python course for people who have some basic programming experience. The goal is to get you up and coding in Python 3, using data science libraries and techniques for machine learning and artificial intelligence applications.
Are you interested in learning Python for Data Science and Machine Learning? Are you worried about not having a programming background or just starting out? Do you want to pivot your career into data science but don’t know where to start? From a bootcamp graduate, we’ve developed this course to help you learn Python and get started in the field of Data Science. Our course starts with the basics of Python, moving through more advanced concepts like machine learning, deep learning, and AI towards building your own project. This unique curriculum was created by a team of experts in order to provide comprehensive training at an affordable price.
The Python for Data Science and Machine Learning Bootcamp is an intensive, five-week training program to help you quickly become proficient in manipulating and analyzing large datasets in Python. This bootcamp provides an essential foundation for building your career in data science, machine learning or any other technology that requires hands-on experience with Python. You’ll get a comprehensive understanding of how to use the different types of machine learning algorithms, such as logistic regression, random forests and neural networks.
Use of Python
Use Python to find insights from data and build intelligent applications—without any prior experience. This hands-on course will help you master the use of Python for data science and machine learning, including gathering and structuring data for analytics. You’ll learn about common machine learning tasks and what it takes to actually implement those tasks in real-world settings
This course is the perfect place to start learning Python for data science and machine learning. You’ll be guided through hands-on examples that use real-life data and build a skill set you can leverage in both your professional and personal life.
Jose Portilla presents an eight-week boot camp designed to get you up and running with Python and machine learning. This course is intended for those with some programming experience who want to apply it in the real world.
For anyone interested in learning Python for data science and machine learning, this course will take you from beginner to advanced. You’ll begin by unravelling the mysteries of programming and end by developing your own practical applications using Python. You’ll learn to think like a computer scientist, as well as discover how to use machine learning models in order to build intelligent computing applications.
Python for Data Science and Machine Learning Bootcamp is your first step to becoming a data scientist. The course covers the essentials of programming in Python, which is the most popular language in data science, along with high-level mathematics and statistics concepts that are essential to becoming a great data scientist.
Our bootcamp allows you to acquire deep technical skills in Python for Data Science and Machine Learning. You will gain practical experience by completing projects in data analysis and visualization, statistical modeling, and machine learning.
This course will fully prepare you to apply Python for any type of data science solution, whether you’re looking to analyze a dataset or build sophisticated machine learning models. Get started by mastering the fundamentals such as functions, variables, and control flow that are essential for all Python applications. Next, you’ll begin working with real-world examples covering image classification, recommendation systems, time series forecasting and more. Finally, this course will teach you how to apply these concepts in different scenarios like web development and data science competitions using Jupyter Notebook.
This course will help you develop data science and machine learning applications using Python. It covers the major aspects of the data science process, including data cleaning and manipulation, exploratory analysis, feature engineering, model training and evaluation and deployment. You’ll learn how to apply different types of machine learning algorithms including supervised classification methods such as SVMs and decision trees, unsupervised algorithms including clustering or PCA.
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