Data Science & Machine Learning using Python 3 : HANDS ON

Rating 4.5 out of 5 (1 ratings in Udemy)

What you'll learn

Become a Data Scientist and get hired
The essence of Artificial Intelligence
The Life Cycle of a Data Scientist
The working of AI models
Hands on Working of ML projects
Ways of Data Visualization
Use Python for Data Science and Machine Learning
Implement Machine Learning Algorithms
Learn to use NumPy for Numerical Data, Pandas for Data Analysis, Matplotlib for Python Plotting, Seaborn for statistical plots, SciKit-Learn for …

Rating 4.5 out of 5 (1 ratings in Udemy)

What you'll learn

Become a Data Scientist and get hired
The essence of Artificial Intelligence
The Life Cycle of a Data Scientist
The working of AI models
Hands on Working of ML projects
Ways of Data Visualization
Use Python for Data Science and Machine Learning
Implement Machine Learning Algorithms
Learn to use NumPy for Numerical Data, Pandas for Data Analysis, Matplotlib for Python Plotting, Seaborn for statistical plots, SciKit-Learn for AI Models
Logistic Regression, Linear Regression, Decision Trees, Support Vector Machines, K-Nearest Neighbors, K Means Clustering, DBSCAN
Fill up your resume with in demand data science skills: Python programming with NumPy, pandas, matplotlib, and Seaborn, Machine Learning Models
Impress interviewers by showing an understanding of the data science field
Learn how to pre-process data, Understand the mathematics behind Machine Learning, Apply your skills to real-life business cases
Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing
Learn how to code in Jupiter Notebooks
Have a great intuition of many Machine Learning models, accurate predictions, powerful analysis, Make robust Machine Learning models
Create strong added value to your business
Build an army of powerful Machine Learning models and know how to combine them to solve any problem
Learn to pre process data, clean data, and analyze large data.
Build a portfolio of work to have on your resume
Supervised and Unsupervised Learning
A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided
Apply the concepts and models you learn in this course in the real world using datasets

Description

Are you ready to transition your career into becoming a Data Scientist ?

This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!

Data scientist is one of the best suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace.

Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!

However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist.

This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 50HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy!

We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning:

Programming with Python
NumPy with Python
Using pandas Data Frames to solve complex tasks
Use pandas to handle Excel Files
Use matplotlib and seaborn for data visualizations
Machine Learning with SciKit Learn, including:
Linear Regression
K Nearest Neighbors
K Means Clustering
Decision Trees
Logistic Regression
DBSCAN
Support Vector Machines and much, much more!

Enroll in the course and become a data scientist today !!!

Duration 8 Hours 58 Minutes

Paid

Self paced

Beginner Level

English (US)

Rating 4.5 out of 5 (1 ratings in Udemy)

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