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Machine Learning A-Z™: AI, Python & R + ChatGPT Bonus

Course From:
Udemy

Interested in the field of Machine Learning? Then this course is for you!

This course has been designed by a Data Scientist and a Machine Learning expert so that we can share our knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.

Over 900,000 students world-wide trust this course.

We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course can be completed by either doing either the Python tutorials, or R tutorials, or both - Python & R. Pick the programming language that you need for your career.

This course is fun and exciting, and at the same time, we dive deep into Machine Learning. It is structured the following way:

  • Part 1 - Data Preprocessing

  • Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression

  • Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification

  • Part 4 - Clustering: K-Means, Hierarchical Clustering

  • Part 5 - Association Rule Learning: Apriori, Eclat

  • Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling

  • Part 7 - Natural Language Processing: Bag-of-words model and algorithms for NLP

  • Part 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural Networks

  • Part 9 - Dimensionality Reduction: PCA, LDA, Kernel PCA

  • Part 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost

Each section inside each part is independent. So you can either take the whole course from start to finish or you can jump right into any specific section and learn what you need for your career right now.

Moreover, the course is packed with practical exercises that are based on real-life case studies. So not only will you learn the theory, but you will also get lots of hands-on practice building your own models.

And as a bonus, this course includes both Python and R code templates which you can download and use on your own projects.

Who this course is for:

  • Anyone interested in Machine Learning.
  • Students who have at least high school knowledge in math and who want to start learning Machine Learning.
  • Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
  • Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.
  • Any students in college who want to start a career in Data Science.
  • Any data analysts who want to level up in Machine Learning.
  • Any people who are not satisfied with their job and who want to become a Data Scientist.
  • Any people who want to create added value to their business by using powerful Machine Learning tools.

 

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Course
Intermediate
Careers

Careers Related to Machine Learning A-Z™: AI, Python & R + ChatGPT Bonus

Certifications

Certifications related to Machine Learning or Python Data Science or Machine Learning Python

Data Science Accelerator

General Assembly’s Data Science part-time course is a practical introduction to the interdisciplinary field of data science and machine learning, which lies at the intersection of computer science, statistics, and business. You will learn to use the Python programming language to acquire, parse, and model data for informing business strategy. 

This is a fast-paced course with some prerequisites. Students should be comfortable with programming fundamentals, core Python syntax, and basic statistics. There is an option to complete up to 25 hours of online preparatory lessons. Talk to the General Assembly Admissions team to discuss your background and confirm if this is the right fit for you..

 

What you'll accomplish

A significant portion of the course is a hands- on approach to fundamental modeling techniques and machine learning algorithms. You’ll also practice communicating your results and insights by compiling technical documentation and a stakeholder presentation. Throughout this expert-designed program, you’ll:

  • Perform exploratory data analysis with Python.
  • Build and refine machine learning models to predict patterns
  • from data sets.
  • Communicate data-driven insights to technical and non-technical audiences alike.
  • Apply what you’ve learned to create a portfolio project: a predictive model that addresses a real-world data problem.

 

Why General Assembly

Since 2011, General Assembly has graduated more than 40,000 students worldwide from the full time & part time courses. During the 2020 hiring shutdown, GA's students, instructors, and career coaches never lost focus, and the KPMG-validated numbers in their Outcomes report reflect it. *For students who graduated in 2020 — the peak of the pandemic — 74.4% of those who participated in GA's full-time Career Services program landed jobs within six months of graduation. General Assembly is proud of their grads + teams' relentless dedication and to see those numbers rising. Download the report here.

 

Your next step? Submit an application to talk to the General Assembly Admissions team


 

Note: reviews are referenced from Career Karma - https://careerkarma.com/schools/general-assembly

 

Udacity
Advanced
3 months
10-15 hours
Data Science Bootcamp

General Assembly’s Data Science Immersive is a transformative course designed for you to get the necessary skills for a data scientist role in three months. 

The Data Science bootcamp is led by instructors who are expert practitioners in their field, supported by career coaches that work with you since day one and enhanced by a career services team that is constantly in talks with employers about their tech hiring needs.

 

What you'll accomplish

As a graduate, you will be ready to succeed in a variety of data science and advanced analytics roles, creating predictive models that drive decision-making and strategy throughout organizations of all kinds. Throughout this expert-designed program, you’ll:

  • Collect, extract, query, clean, and aggregate data for analysis.
  • Gather, store and organize data using SQL and Git.
  • Perform visual and statistical analysis on data using Python and its associated libraries and tools.
  • Craft and share compelling narratives through data visualization.
  • Build and implement appropriate machine learning models and algorithms to evaluate data science problems spanning finance, public policy, and more.
  • Compile clear stakeholder reports to communicate the nuances of your analyses.
  • Apply question, modeling, and validation problem-solving processes to data sets from various industries to provide insight into real-world problems and solutions.
  • Prepare for the world of work, compiling a professional-grade portfolio of solo, group, and client projects.

 

Why General Assembly

Since 2011, General Assembly has graduated more than 40,000 students worldwide from the full time & part time courses. During the 2020 hiring shutdown, GA's students, instructors, and career coaches never lost focus, and the KPMG-validated numbers in their Outcomes report reflect it. *For students who graduated in 2020 — the peak of the pandemic — 74.4% of those who participated in GA's full-time Career Services program landed jobs within six months of graduation. General Assembly is proud of their grads + teams' relentless dedication and to see those numbers rising. Download the report here.

 

Your next step? Submit an application to talk to the General Assembly Admissions team


 

Note: reviews are referenced from Career Karma - https://careerkarma.com/schools/general-assembly

 

Udacity
Advanced
3 months
10-15 hours
Natural Language Processing Expert

Learn cutting-edge natural language processing techniques to process speech and analyze text. Build probabilistic and deep learning models, such as hidden Markov models and recurrent neural networks, to teach the computer to do tasks such as speech recognition, machine translation, and more!

Udacity
Advanced
3 months
10-15 hours
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