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## Python for Data Science and Machine Learning Bootcamp: Udemy Machine Learning Course

Have you already chosen your path to become a data scientist? This Python for Data Science and Machine Learning Bootcamp, Udemy Machine Learning comprehensive course can be your best guide to learning how to use the power of Python to analyze data, create beautiful visuals, and use powerful machine learning algorithms! Glassdoor has ranked Data Scientist as number one job and Data Scientist’s average salary is over $ 120,000 in the United States. Data scientist is a rewarding career that allows you to solve some of the most interesting problems in the world. This Python for Data Science and Machine Learning Bootcamp course is designed for both beginners having some programming skill or experienced developers who have already made the leap into data science career.

### Skills you can get from Python for Data Science and Machine Learning Bootcamp: Udemy Machine Learning

- Use Python for Data Science and Machine Learning
- Implement Machine Learning Algorithms
- Learn to use Pandas for Data Analysis
- Learn to use Seaborn for statistical plots
- Use SciKit-Learn for Machine Learning Tasks
- Logistic Regression
- Random Forest and Decision Trees
- Neural Networks
- Use Spark for Big Data Analysis
- Learn to use NumPy for Numerical Data
- Learn to use Matplotlib for Python Plotting
- Use Plotly for interactive dynamic visualizations
- K-Means Clustering
- Linear Regression
- Natural Language Processing and Spam Filters
- Support Vector Machines

PLATFORM: | UDEMY |

PROVIDER: | JOSE PORTILLA |

COST: | $11.99 (94%OFF) |

DIFFICULTY: | BEGINNER |

LANGUAGE: | 8 LANGUAGES |

CERTIFICATE: | AVAILABLE |

EFFORT: | 25 HOURS |

START DATE: | ON GOING |

**GRAB THE DISCOUNT**

The Python for Data Science and Machine Learning Bootcamp comprehensive course is priceless and similar to other data science bootcamps, which typically cost thousands of dollars. Now you can get all that knowledge and information at a fraction of the cost with this Python for Data Science and Machine Learning Bootcamp course. There are more than 100 HD video lectures and detailed code notebooks for every single lecture, which makes this course one of the most comprehensive courses for data science and machine learning available on Udemy.

Jose Portilla, the instructor for Python for Data Science and Machine Learning Bootcamp will teach you how to program with Python, how to create amazing data visualizations, and how to use machine learning with Python. This course Python for Data Science and Machine Learning Bootcamp is meant for people with at least some programming experience but not mandatory. Here are some of the topics that you are going to learn:

- Programming with Python
- NumPy with Python
- Using pandas Data Frames to solve complex tasks
- Use pandas to handle Excel Files
- Web scraping with python
- Connect Python to SQL
- Use matplotlib and seaborn for data visualizations
- Use plotly for interactive visualizations

- Machine Learning with SciKit Learn, including:
- Linear Regression
- K Nearest Neighbors
- K Means Clustering
- Decision Trees
- Random Forests
- Natural Language Processing
- Neural Nets and Deep Learning
- Support Vector Machines
- and much, much more!

### Syllabus of Python for Data Science and Machine Learning Bootcamp

Course Introduction — 3 Lectures 7 Min

Environment Set-Up — 1 Lecture 11 Min

Jupyter Overview — 3 Lectures 24 Min

Python Crash Course — 8 Lectures 1 Hour 24 Min

Python for Data Analysis – NumPy — 8 Lectures 1 Hour 4 Min

Python for Data Analysis – Pandas — 11 Lectures 1 Hour 43 Min

Python for Data Analysis – Pandas Exercises — 5 Lectures 35 Min

Python for Data Visualization – Matplotlib — 7 Lectures 1 Hour

Python for Data Visualization – Seaborn — 9 Lectures 1 Hour 22 Min

Python for Data Visualization – Pandas Built-In Data Visualization — 3 Lectures 24 Min

Python for Data Visualization – Plotly and Cufflinks — 3 Lectures 22 Min

Python for Data Visualization – Geographical Plotting — 5 Lectures 40 Min

Data Capstone project — 9 Lectures 1 Hour 19 Min

Introduction to Machine Learning — 6 Lectures 41 Min

Linear Regression — 6 Lectures 52 Min

Cross Validation and Bias-Variance Trade-Off — 1 Lecture 6 Min

Logistic regression — 6 Lectures 1 Hour 7 Min

K Nearest Neighbors — 4 Lectures 41 Min

Decision Trees and Random Forests — 5 Lectures 45 Min

Support Vector Machines — 4 Lectures 35 Min

K Means Clustering — 4 Lectures 35 Min

Principal Component Analysis — 2 Lectures 20 Min

Recommender Systems — 3 Lectures 31 Min

Natural Language Processing — 6 Lectures 1 Hour 19 Min

Neural Nets and Deep Learning — 30 Lectures 5 hours 2 Min

Big Data and Spark with Python — 12 Lectures 1 Hour and 42 Min

Bonus Section: Thank You — 1 Lecture 1 Min