Python for Data Science & Machine Learning from A-Z paid course free. You will become a professional Data Scientist and learn how to use NumPy, Pandas, Machine Learning, and more!
- 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
- Probability and Hypothesis Testing
Python for Data Science & Machine Learning from A-Z Course Requirements
- Students should have basic computer skills
- Students would benefit from having prior Python Experience but not necessary
Python for Data Science & Machine Learning from A-Z Course Description
Learn Python for Data Science & Machine Learning from A-Z
In this hands-on course, you will learn to use Python for data science and machine learning programming. This includes data analysis, visualization, and how to use this data in a practical way. Our main goal is to provide you with education, not only to understand the ins and outs of the Python programming language in data science and machine learning but also to understand exactly how to use Python to become a professional data scientist and find your first job.
We will review some of the best and most important Python libraries for data science, such as NumPy, Pandas, and Matplotlib + NumPy: a library that promotes various mathematical and statistical operations; it is also the basis for many functions of the panda’s library. Pandas-A Python library created specifically to simplify data processing, which is the basis of many Python data science jobs. NumPy and Pandas are very suitable for exploring and playing with data. Matplotlib is a data visualization library that can create charts you find in Excel or Google Sheets.
Combining hands-on work with a strong theoretical background, we will take you from basic knowledge of Python data science programming to mastery. This Python machine learning course delves into the basics of Python machine learning. You will learn about supervised and unsupervised. Unsupervised learning, see how statistical modeling relates to machine learning, and compare each. We understand that theory is important to build a solid foundation, and we understand that theory alone will not work, so this course is full of practical examples that you can follow step by step.
Even if you already have some coding experience or want to understand the advanced features of the Python programming language, this course is for you! Job vacancies such as data scientists, machine learning engineers, big data engineers, IT experts, database developers, etc. require or recommend Python coding experience.
Adding Python coding language skills to your resume will help you complete any data major that requires mastery of statistical techniques. We will provide you with basic education, you not only need to understand writing Python code, analyzing and visualizing data. And the use of machine learning algorithms, and how to charge for your newly developed programming skills.
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
- 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
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
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.
Who this course is for:
- Students who want to learn about Python for Data Science & Machine Learning
Python for Data Science & Machine Learning from A-Z
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