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# build your AI skills: beginner to expert;
aiplus.build(_name)
aiplus.train(_name)
aiplus.test(_name)
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Live and on-demand training in:
MACHINE LEARNING
 DATA SCIENCE
 DEEP LEARNING
DATA ANALYTICS
 DATA ENGINEERING
NLP & NLU
RESPONSIBLE AI
CYBERSECURITY
COMPUTER VISION
ROBOTICS
Available On-Demand
Data is the essential building block of Data Science, Machine Learning, and AI. This course is the first in the series and is designed to teach you the foundational skills and knowledge required to understand, work with, and analyze data.Â
Available On-Demand
his SQL coding course teaches students the basics of Structured Query Language, which is a standard programming language used for managing and manipulating data and an essential tool in AI. You will learn how to design and write SQL codeÂ
Available On-Demand
The Python language is one of the most popular programming languages in data science and machine learning as it offers a number of powerful and accessible libraries and frameworks specifically designed for these fields.Â
Now Available On-demand
Network traffic data can be a rich source of information for cybersecurity and IT management. Malware is delivered and performs command and control communications over the network, and software sends and receives a wealth of data over the network.
The course provides an introduction to analyzing network traffic data with Python. Python is an ideal tool for this task because it is freely available and has numerous modules that support network traffic analysis, data science, and other tasks.
This course will build familiarity and skills in network traffic analysis via a series of hands-on exercises and examples. By examining, modifying, and building custom scripts for network traffic analysis, you’ll how to access and select network traffic data, analyze it, and interpret the results.
Now Available On-demand
By the end of this 4-part live, hands-on, online course, you’ll understand in detail how Gradient Boosting models are fit as an ensemble of decision trees and apply that understanding to the feature engineering process, the various parameters of Gradient Boosting and their relative importance and how to appropriately choose them and gain familiarity with the various Gradient Boosting packages and the capabilities, strengths, and weaknesses of each. You will also learn how to interpret, understand, and evaluate a model: both qualitatively and quantitatively.
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ATTEND DATA ENGINEERING LIVE SUMMITLIVE TRAINING:Â June 10th, 2021
Part 2: Computer Science
Through the measured exposition of theory paired with interactive examples, you’ll develop a working understanding of all of the essential data structures across the list, dictionary, tree, and graph families
LIVE TRAINING:Â JUNE 15th, 2021
Matt Brems will cover introduction to Natural Language Processing including cleaning text data, transforming data with CountVectorizer and and TFIDFVectorizer as well as how to Fit machine learning models in scikit-learn and evaluate their performance. You will also learn how to build pipelines and GridSearch over NLP hyperparameters.
TOP RATED ON-DEMAND BOOTCAMP
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This 6-weeks Bootcampis  an introduction to deep neural networks that brings high-level theory to life with working, interactive examples featuring TensorFlow 2, Keras, and PyTorch — all three of the principal Python libraries for deep learning. Essential theory will be covered in a manner that provides students with a complete intuitive understanding of deep learning’s underlying foundations.
Paired with hands-on code demos in Jupyter notebooks as well as strategic advice for overcoming common pitfalls, this foundational knowledge will empower individuals with no previous understanding of artificial neural networks to build production-ready deep learning applications across all of the contemporary families
Taught by renowned, expert instructors:
Live training student experience
Time Series Forecasting with Python
All clear and well explained by our very knowledgable instructor, Marta. This was all extremely applicable to my job. Wish this was a full day instead as Marta had a lot of amazing content. Thanks to the instructor and organizers.

Micheleen Harris
Hands-On Intro to Unsupervised Learning
I had a bit of previous experience with some of the techniques and was looking for more in-depth. Got all I wanted. Ankur has a great presentation style and excellent examples. I particularly appreciated Ankur’s answers to my numerous questions. Those answers alone were worth the price because they provided insight into real-world applications of these models. I also liked the use of live demo in the TensorFlow projector to visualize the results of every algorithm. Will adopt it right away.

Michael Livshutz
NLP Fundamentals in Python
Matt took us through difficult terrain with ease, making sure everybody was on the same page throughout. Really great teaching! Incredibly useful!

Huw Hallam
Advanced Fraud Modeling
Aric is a great teacher and the entire class was structured very well. I learned a lot of new interesting techniques. A mix of lecture and live coding with real-time incorporation of student feedback and questions into the class. Best for intermediate to advanced data folks because it assumes you know some Python. I would highly recommend if you have an interest to learn fraud.

Shery Cheong
Practical Advanced Pandas
I like the hands-on approach to teaching the additional techniques of Pandas, and I greatly appreciate the availability of the course’s code for me to review later.

Tyrel Cherry
The #1 Machine Learning Mini-Bootcamp
