Artificial Intelligence (AI):
artificial-intelligence, Machine Learning, Python, Deep Learning, ML, AI , DL, NLP, Natural Language Process.
This Artificial Intelligence course provides training in the skills required for a career in AI. You will master TensorFlow, Machine Learning, and other AI concepts, plus the programming languages needed to design intelligent agents, deep learning algorithms & advanced artificial neural networks that use predictive analytics to solve real-time decision-making problems.

What skills will you learn?

By the end of this Artificial Intelligence Course, you will be able to accomplish the following: 
  • Design and build your own intelligent agents and apply them to create practical AI projects including  games, machine learning models, logic constraint satisfaction problems, knowledge-base systems, probabilistic models, agent decision-making functions and more
  • Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
  • Understand and master the concepts and principles of  machine learning, including its mathematical and heuristic aspects
  • Implement deep learning algorithms in TensorFlow and interpret the results,
  • Understand neural networks and multi-layer data abstraction, empowering you to analyze and utilize data like never before
  • Comprehend and differentiate between theoretical concepts and practical aspects of machine learning, 
  • Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces
  • Learn about major applications of Artificial Intelligence across various use cases in various fields like customer service, financial services, healthcare etc
  • Implement classical Artificial Intelligence techniques, such as search algorithms, minimax algorithm, neural networks, tracking, robot localization
  • Ability to apply Artificial Intelligence techniques for problem-solving and explain the limitations of current Artificial Intelligence techniques
  • Formalise a given problem in the language/framework of different AI methods (e.g., as a search problem, as a constraint satisfaction problem, as a planning problem, etc)
  • Master skills and tools used by the most innovative AI teams across the globe as you delve into specializations, and gain experience solving real-world challenges.

Artificial Intelligence like Supervised Learning, Unsupervised Learning, Reinforcement Learning, Support Vector Machines, Deep Learning, TensorFlow, Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks.

What projects are included in this program?

This Artificial Intelligence Master’s program includes 5+ real-life, branded industry-based projects on different domains to help you master concepts of Artificial Intelligence like Supervised Learning, Unsupervised Learning, Reinforcement Learning, Support Vector Machines, Deep Learning, TensorFlow, Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks. A few of the projects, that you will be working on are mentioned below:
Capstone Project:
Description: You will go through dedicated mentored classes in order to create a high-quality industry project, solving a real-world problem leveraging the skills and technologies learnt throughout the program. The capstone project will cover all the key aspects from exploratory data analysis to model creation and fitting. As a learner, you will cover cutting edge AI-based supervised and unsupervised algorithms like Regression, Multinomial Naïve Bayes, SVM, Tree-based algorithms, NLP, etc. You also get the option of choosing the domain/industry dataset you to want to work on from the options available. After successful submission of the project, you will be awarded a capstone certificate that can be showcased to potential employers as a testament to your learning.
Project 1: Fare Prediction for Uber
Domain: Delivery (Commerce)
Uber, one of the largest US-based taxi cab provider, wants to improve the accuracy of fare predicted for any of the trips. Help Uber by building and choosing the right model.
Project 2: Test bench time reduction for Mercedes-Benz
Domain: Automobile
Mercedes-Benz, a global Germany based automobile manufacturer, wants to reduce the time it spends on the test bench for any car. Faster testing will reduce the time to hit the market. Build and optimise the algorithm by performing dimensionality reduction and various techniques including xgboost to achieve the said objective. 
Project 3: Products rating prediction for Amazon
Amazon, one of the leading US-based e-commerce companies, recommends products within the same category to customers based on their activity and reviews on other similar products. Amazon would like to improve this recommendation engine by predicting ratings for the non-rated products and add them to recommendations accordingly.
Domain: E-commerce
Project 4: Demand Forecasting for Walmart
Predict accurate sales for 45 stores of Walmart, one of the US-based leading retail stores, considering the impact of promotional markdown events. Check if macroeconomic factors like CPI, unemployment rate, etc. have an impact on sales.
Domain: Sales
Project 5: Improving customer experience for Comcast
Comcast, one of the US-based global telecommunication companies wants to improve customer experience by identifying and acting on problem areas that lower customer satisfaction if any. The company is also looking for key recommendations that can be implemented to deliver the best customer experience.
Domain: Telecom
Project 6: Attrition Analysis for IBM
IBM, one of the leading US-based IT companies, would like to identify the factors that influence attrition of employees. Based on the parameters identified, the company would also like to build a logistics regression model that can help predict if an employee will churn or not.
Domain: Workforce Analytics
Project 7: NYC 311 Service Request Analysis
Perform a service request data analysis of New York City 311 calls. You will focus on data wrangling techniques to understand patterns in the data and visualize the major complaint types.
Domain: Telecommunication
 
Project 8: MovieLens Dataset Analysis
The GroupLens Research Project is a research group in the Department of Computer Science and Engineering at the University of Minnesota. The researchers of this group are involved in several research projects in the fields of information filtering, collaborative filtering and recommender systems. Here, we ask you to perform an analysis using the Exploratory Data Analysis technique for user datasets.
Domain: Engineering
 
Project 9: Stock Market Data Analysis
As a part of this project, you will import data using Yahoo data reader from the following companies: Yahoo, Apple, Amazon, Microsoft and Google. You will perform fundamental analytics, including plotting, closing price, plotting stock trade by volume, performing daily return analysis, and using pair plot to show the correlation between all of the stocks.
Domain: Stock Market

What are the prerequisites for this Artificial Intelligence course?

Participants in this course should have:

  • Understanding of the fundamentals of Python programming 
  • Basic knowledge of statistics
  • Basic machine learning knowledge