Artificial Intelligence Engineer

This co-developed Simplilearn and IBM Artificial Intelligence Engineer Master’s Program is a blend of Artificial Intelligence, Data Science, Machine Learning, and Deep Learning, enabling the real-world implementation of advanced tools and models. The AI certification course is designed to give you in-depth knowledge of Artificial Intelligence concepts including the essentials of statistics required for Data Science, Python programming, and Machine Learning. Through these AI courses, you will learn how to use Python libraries like NumPy, SciPy, Scikit, and essential Machine Learning techniques, such as supervised and unsupervised learning, advanced concepts covering artificial neural networks, and layers of data abstraction and TensorFlow. 

Artificial intelligence and Machine Learning will impact all segments of daily life by 2025, with applications in a wide range of industries such as healthcare, transportation, insurance, transport and logistics, and customer service. A role in this domain places you on the path to an exciting, evolving career that is predicted to grow sharply into 2025 and beyond. 

• Understand the meaning, purpose, scope, stages, applications, and effects of Artificial Intelligence
   
• Design and build your own intelligent agents, applying them to create practical Artificial Intelligence projects, including games, machine learning models, logic constraint satisfaction problems, knowledge-based systems, probabilistic models, and agent decision-making functions
   
• Master the essential concepts of Python programming, including data types, tuples, lists, dicts, basic operators, and functions
   
• Learn how to write your own Python scripts and perform basic hands-on data analysis using Jupyter notebook
   
• Gain an in-depth understanding of Data Science processes: data wrangling, data exploration, data visualization, hypothesis building, and testing
   
• Perform high-level mathematical and technical computing using the NumPy and SciPy packages and data analysis with the Pandas package
   
• Master the concepts of supervised and unsupervised learning models, including linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipeline, recommendation engine, and time series modeling
   
• Understand the concepts of TensorFlow, its main functions, operations, and the execution pipeline
   
• Master advanced topics in Artificial Intelligence, such as convolutional neural networks, recurrent neural networks, training deep networks, and high-level interfaces

This Artificial Intelligence Engineer Master's program co-developed with IBM includes over 15 real-life, branded projects in different domains. These projects are designed to help you master the key concepts of Artificial Intelligence like supervised and unsupervised learning, reinforcement learning, support vector machines, Deep Learning, TensorFlow, neural networks, convolutional neural networks, and recurrent neural networks. 

This AI Engineer Master’s Program includes a capstone project allowing you to revisit the concepts learned throughout the courses. You will go through dedicated mentored classes in order to create a high-quality industry project, solving a real-world problem. The capstone project will cover key aspects from exploratory data analysis to model creation and fitting. To complete this capstone project, you will use cutting edge Artificial Intelligence-based supervised and unsupervised algorithms like Regression, Multinomial Naive Bayes, SVM, Tree-based algorithms, and NLP in the domain of your choice. After successful submission of the project, not only will you be awarded a capstone certificate but you will have a project 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 providers, 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 optimize the algorithm by performing dimensionality reduction and various techniques including xgboost to achieve the said objective. 

Project 3: Products rating prediction for Amazon | Domain: E-commerce

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.

Project 4: Demand Forecasting for Walmart | Domain: Sales

Predict accurate sales for 45 stores of Walmart, one of the leading 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.

Project 5: Improving customer experience for Comcast | Domain: Telecom

Comcast, one of the leading 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.

Project 6: Attrition Analysis for IBM | Domain: Workforce Analytics

IBM, one of the leading US-based IT companies, would like to identify the factors that influence the 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.

Project 7: NYC 311 Service Request Analysis | Domain: Telecommunication

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.

 Project 8: MovieLens Dataset Analysis | Domain: Engineering

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.

Project 9: Stock Market Data Analysis | Domain: Stock Market

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.

Participants in this AI certification course should have:

• An understanding of the fundamentals of Python programming 
• Basic knowledge of statistics

• Artificial Intelligence Engineer
   
• Data Scientist
   
• Analytics Manager/Lead
   
• Machine Learning Engineer
   
• Statistical Programming Specialist