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22 Hours
140 Lesson
Learn Python for Data Science & Machine Learning from A-Z
In this practical, hands-on course you’ll learn how to program using Python for Data Science and Machine Learning. This includes data analysis, visualization, and how to make use of that data in a practical manner.
Our main objective is to give you the education not just to understand the ins and outs of the Python programming language for Data Science and Machine Learning, but also to learn exactly how to become a professional Data Scientist with Python and land your first job.
We'll go over some of the best and most important Python libraries for data science such as NumPy, Pandas, and Matplotlib +
NumPy — A library that makes a variety of mathematical and statistical operations easier; it is also the basis for many features of the pandas library.
Pandas — A Python library created specifically to facilitate working with data, this is the bread and butter of a lot of Python data science work.
NumPy and Pandas are great for exploring and playing with data. Matplotlib is a data visualization library that makes graphs as you’d find in Excel or Google Sheets. Blending practical work with solid theoretical training, we take you from the basics of Python Programming for Data Science to mastery.
This Machine Learning with Python course dives into the basics of machine learning using Python. You'll learn about supervised vs. unsupervised learning, look into how statistical modeling relates to machine learning, and do a comparison of each.
We understand that theory is important to build a solid foundation, we understand that theory alone isn’t going to get the job done so that’s why this course is packed with practical hands-on examples that you can follow step by step. Even if you already have some coding experience, or want to learn about the advanced features of the Python programming language, this course is for you!
Python coding experience is either required or recommended in job postings for data scientists, machine learning engineers, big data engineers, IT specialists, database developers, and much more. Adding Python coding language skills to your resume will help you in any one of these data specializations requiring mastery of statistical techniques.
Together we’re going to give you the foundational education that you need to know not just on how to write code in Python, analyze and visualize data and utilize machine learning algorithms but also how to get paid for your newly developed programming skills.
The course covers 5 main areas:
1: PYTHON FOR DS+ML COURSE INTRO
This intro section gives you a full introduction to the Python for Data Science and Machine Learning course, data science industry, and marketplace, job opportunities and salaries, and the various data science job roles.
Intro to Data Science + Machine Learning with Python
Data Science Industry and Marketplace
Data Science Job Opportunities
How To Get a Data Science Job
Machine Learning Concepts & Algorithms
2: PYTHON DATA ANALYSIS/VISUALIZATION
This section gives you a full introduction to the Data Analysis and Data Visualization with Python with hands-on step by step training.
Python Crash Course
NumPy Data Analysis
Pandas Data Analysis
3: MATHEMATICS FOR DATA SCIENCE
This section gives you a full introduction to the mathematics for data science such as statistics and probability.
Descriptive Statistics
Measure of Variability
Inferential Statistics
Probability
Hypothesis Testing
4: MACHINE LEARNING
This section gives you a full introduction to Machine Learning including Supervised & Unsupervised ML with hands-on step-by-step training.
Intro to Machine Learning
Data Preprocessing
Linear Regression
Logistic Regression
K-Nearest Neighbors
Decision Trees
Ensemble Learning
Support Vector Machines
K-Means Clustering
PCA
5: STARTING A DATA SCIENCE CAREER
This section gives you a full introduction to starting a career as a Data Scientist with hands-on step by step training.
Creating a Resume
Creating a Cover Letter
Personal Branding
Freelancing + Freelance websites
Importance of Having a Website
Networking
By the end of the course you’ll be a professional Data Scientist with Python and confidently apply for jobs and feel good knowing that you have the skills and knowledge to back it up.
Students should have basic computer skills
Students would benefit from having prior Python Experience but not necessary
Students who want to learn about Python for Data Science & Machine Learning
Become a professional Data Scientist, Data Engineer, Data Analyst or Consultant
Learn data cleaning, processing, wrangling and manipulation
How to create resume and land your first job as a Data Scientist
How to use Python for Data Science
How to write complex Python programs for practical industry scenarios
Learn Plotting in Python (graphs, charts, plots, histograms etc)
Learn to use NumPy for Numerical Data
Machine Learning and it's various practical applications
Supervised vs Unsupervised Machine Learning
Learn Regression, Classification, Clustering and Sci-kit learn
Machine Learning Concepts and Algorithms
K-Means Clustering
Use Python to clean, analyze, and visualize data
Building Custom Data Solutions
Statistics for Data Science
Introduction
7 Lessons
1H 11M
Data Science & Machine Learning Concepts
6 Lessons
1H 6M
3m 14s
13m 24s
14m 22s
9m 44s
Python For Data Science
19 Lessons
3H 35M
6m 3s
3m 54s
3m 27s
25m 26s
13m 12s
5m 10s
15m 8s
11m 25s
20m 19s
9m 41s
14m 23s
Statistics for Data Science
8 Lessons
1H 8M
7m 11s
6m 35s
12m 19s
15m 18s
1m 57s
7m 34s
Probability & Hypothesis Testing
4 Lessons
0H 20M
2m 38s
5m 15s
NumPy Data Analysis
6 Lessons
0H 52M
12m 58s
8m 21s
11m 36s
9m 10s
5m 53s
4m 32s
Pandas Data Analysis
2 Lessons
0H 33M
15m 52s
Python Data Visualization
3 Lessons
0H 46M
Machine Learning
1 Lessons
0H 26M
Data Loading & Exploration
1 Lessons
0H 13M
Data Cleaning
2 Lessons
0H 15M
7m 40s
7m 43s
Feature Selecting and Engineering
1 Lessons
0H 6M
6m 11s
Linear and Logistic Regression
5 Lessons
0H 49M
8m 17s
5m 58s
3m 22s
K Nearest Neighbors
13 Lessons
1H 36M
3m 1s
22m 8s
2m 16s
3m 32s
5m 32s
Decision Trees
16 Lessons
2H 51M
16m 53s
10m 15s
17m 11s
2m 49s
Ensemble Learning and Random Forests
13 Lessons
1H 44M
5m 20s
4m 41s
4m 10s
14m 33s
Support Vector Machines
10 Lessons
1H 41M
5m 16s
11m 38s
13m 25s
4m 17s
12m 18s
18m 13s
12m 50s
5m 51s
K-means
3 Lessons
1H 0M
PCA
12 Lessons
2H 0M
5m 12s
9m 36s
3m 31s
2m 50s
14m 31s
7m 31s
Data Science Career
8 Lessons
0H 35M
5m 35s
4m 2s
2m 56s
Dragon Zap Instructor
Hi I'm Juan. I've been an Entrepreneur since grade school. My background is in the tech space from Digital Marketing, E-commerce, Web Development to Programming. I believe in continuous education with the best of a University Degree without all the downsides of burdensome costs and inefficient methods. I look forward to helping you expand your skillsets.
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