Course Description

Complete A.I. & Machine Learning, Data Science Bootcamp

Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries). This course is focused on efficiency: never spend time on confusing, out of date, incomplete Machine Learning tutorials anymore. We are pretty confident that this is the most comprehensive and modern course you will find on the subject anywhere (bold statement, we know).

This comprehensive and project-based course will introduce you to all of the modern skills of a Data Scientist and along the way, we will build many real world projects to add to your portfolio. You will get access to all the code, workbooks and templates (Jupyter Notebooks) on Github, so that you can put them on your portfolio right away! We believe this course solves the biggest challenge to entering the Data Science and Machine Learning field: having all the necessary resources in one place and learning the latest trends and on the job skills that employers want.

The curriculum is going to be very hands on as we walk you from start to finish of becoming a professional Machine Learning and Data Science engineer. The course covers 2 tracks. If you already know programming, you can dive right in and skip the section where we teach you Python from scratch. If you are completely new, we take you from the very beginning and actually teach you Python and how to use it in the real world for our projects. Don’t worry, once we go through the basics like Machine Learning 101 and Python, we then get going into advanced topics like Neural Networks, Deep Learning and Transfer Learning so you can get real life practice and be ready for the real world (We show you fully fledged Data Science and Machine Learning projects and give you programming Resources and Cheatsheets)!

Provider

udemy

Target

  • Aspiring data scientists and machine learning engineers
  • Beginners with no prior programming experience
  • Individuals with some programming knowledge wanting to deepen their understanding of data science
  • Professionals looking to transition into data science or machine learning roles

Sector

  • Data Science
  • Machine Learning
  • Artificial Intelligence (AI)
  • Technology/Information Technology (IT)

Area

  • Data exploration and visualization
  • Neural networks and deep learning
  • Model evaluation and analysis
  • Programming in Python
  • Machine learning libraries (TensorFlow, Scikit-Learn, etc.)
  • Data science projects and workflows
    Supervised and unsupervised learning techniques
  • Data preparation and cleaning
  • Advanced topics like transfer learning and ensemble learning
  • Real-world applications and project development

Method

Online

Certification

Yes

Duration

43.5 hours on-demand video

Assessment

No

Cost

98.99

Learning Outcomes

  • Become a Data Scientist and get hired
  • Master Machine Learning and use it on the job
  • Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0
  • Use modern tools that big tech companies like Google, Apple, Amazon and Meta use
  • Present Data Science projects to management and stakeholders
  • Learn which Machine Learning model to choose for each type of problem
  • Real life case studies and projects to understand how things are done in the real world
  • Learn best practices when it comes to Data Science Workflow
  • Implement Machine Learning algorithms
  • Learn how to program in Python using the latest Python 3
  • How to improve your Machine Learning Models
  • Learn to preprocess data, clean data, and analyze large data.
  • Build a portfolio of work to have on your resume
  • Developer Environment setup for Data Science and Machine Learning
  • Supervised and Unsupervised Learning
  • Machine Learning on Time Series data
  • Explore large datasets using data visualization tools like Matplotlib and Seaborn
  • Explore large datasets and wrangle data using Pandas
  • Learn NumPy and how it is used in Machine Learning

Learning Content

  • Introduction
  • Machine Learning 101
  • Machine Learning and Data Science Framework
  • Data Science Environment Setup
  • Pandas: Data Analysis
  • Matplotlib: Plotting and Data Visualization
  • Scikit-learn: Creating Machine Learning Models
  • Supervised Learning: Classification + Regression
  • Milestone Project 1: Supervised Learning (Classification)
  • Milestone Project 2: Supervised Learning (Time Series Data)
  • Data Engineering
  • Neural Networks: Deep Learning, Transfer Learning and TensorFlow
  • Storytelling + Communication: How to Present Your Work
  • Career Advice + Extra Bits
  • Learn Python49 lectures
  • Learn Python Part 25
  • Extra: Learn Advanced Statistics and Mathematics