New Live Bootcamp: Introduction to Data Science and Machine Learning Bootcamp!
Perfect to get started in the field!
It is almost Christmas, so it is time for a little gift! I am launching a new live bootcamp: Introduction to Data Science and Machine Learning Bootcamp! The BootCamp will start on January 22nd, 2025, and the early-bird pricing (25% off) will last until January 4th, 2025 (apply the coupon EARLY-BIRD). We will meet from January 22nd to February 27th, every Wednesday and Thursday between 3 p.m. and 6 p.m. PST. This is going to be 6 weeks of intense hands-on learning to take the first step into the world of data science and machine learning!
We are going to learn how to manipulate and visualize data to extract the right information from it efficiently. We are then going to introduce the basics of probability theory and statistical inference, as those are the foundational mathematical tools used in data science and machine learning. Finally, we are going to focus on the principles behind supervised learning and unsupervised learning. We are going to learn how to validate model performance and the strategies to improve it with feature engineering.
This boot camp is meant for engineers, data analysts, or students who want to pivot toward a data science and machine learning career! This Bootcamp is not meant to be easy! Be ready to spend time and effort in learning the subject so that the certificate means something.
I won't promise you that you will get a job after graduating (because it depends on you), but I can promise you that your data science and machine learning skills will be at a completely different level!
When designing this course, my goal was to provide the practical set of tools and knowledge to enable beginners to start working on data science projects!
I favor a hands-on approach where students have the opportunity to solve difficult problems close to the ones seen on the job. What I want is to prepare the students to actually be performant on the job.
This boot camp is meant to have a lower barrier to entry and is quite complementary to the Machine Learning Fundamentals BootCamp!
Here are the pre-requisite to get into this boot camp:
Proficiency in Python - at least 6 months experience.
Comfortable with mathematical notation - at least 1st year college level in mathematics.
Here is the curriculum (may be subject to slight changes):
Data Wrangling (1 week)
Any Data Science and Machine Learning project starts with becoming an expert on the data. We are going to dive into the different techniques to slice and dice the data with Pandas:
Exploratory Data Analysis
Advanced Data Manipulation
Data Visualization (0.5 week)
Visualizing the data allows one to uncover unexpected mechanisms and to present results in a more explicitly and transparent manner:
Data visualization with Matplotlib
Data visualization with Seaborn
Probability and Statistics (1.5 weeks)
A solid grounding in probability and statistics is essential for interpreting data, building models, and making data-driven decisions:
Probability Fundamentals
Descriptive Statistics
Statistical Inference
Supervised Learning (1 week)
Supervised learning is at the core of 99% of ML projects in the industry. It involves building predictive models with labeled data.
Regression and Classification models
Model quality estimation
Unsupervised Learning (1 week)
Unsupervised learning captures concepts like clustering and dimension reduction. It is about discovering patterns and structures in unlabeled data.
Clustering
Dimension reduction
Feature Engineering (1 week)
Feature engineering is about preparing the data to train a model. We need to be able to deal with categorical variables and missing values, and we need to extract the right features or create better ones:
Feature Extraction and Selection
Encoding Techniques
Scaling and Normalization
If you have any questions, don’t hesitate to send me an email at damienb@theaiedge.io. Hope to see you there!