This specialization focuses on equipping data scientists and analysts with the skills to preprocess data, handle big data technologies, and implement deep learning models. Learners will gain hands-on experience in data preparation, analysis, and building neural networks for predictive analytics. Industry-relevant tools and techniques will be covered to ensure practical application in real-world scenarios.
Data Analytics and Deep Learning Specialization
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Data Analytics and Deep Learning Specialization
Master Data Analytics and Deep Learning Techniques. Learn advanced data preprocessing, big data technologies, and deep learning to build predictive models and analyze complex datasets.
Instructors: Ming-Long Lam
Included with 
Get in-depth knowledge of a subject
Intermediate level
Recommended experience
6 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
Intermediate level
Recommended experience
6 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
How to preprocess and analyze data using various techniques
Implementation of big data technologies like Hadoop and Spark
Application of deep learning models to solve complex problems
Overview
Skills you'll gain
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
Recently updated!
May 2025
118 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Illinois Tech
Specialization - 3 course series
What you'll learn
1. Apply appropriate techniques for generating insights from data.
2. Present actionable solutions with confidence to the business stakeholders.
Skills you'll gain
Category: Data Analysis
Category: Data Mining
Category: Feature Engineering
Category: Decision Tree Learning
Category: Unsupervised Learning
Category: Regression Analysis
Category: Analytics
Category: Data Cleansing
Category: Machine Learning
Category: Data Visualization
Category: Machine Learning Algorithms
Category: Data Manipulation
Category: Scikit Learn (Machine Learning Library)
Category: Applied Machine Learning
Category: Statistical Analysis
Category: Data Presentation
Category: Statistical Modeling
Category: Exploratory Data Analysis
Category: Python Programming
Category: Data Science
What you'll learn
Understanding and identifying use cases and domains of Big Data problems
Selecting and implementing technical solutions involving Big Data systems
Develop and use various open source software systems (Apache) in the Big Data tech stack
Operate and run various cloud computing software services (AWS) in the Big Data infrastructure space
Skills you'll gain
Category: Apache Spark
Category: NoSQL
Category: Distributed Computing
Category: Apache Hadoop
Category: Big Data
Category: MongoDB
Category: Real Time Data
Category: Data Lakes
Category: Data Processing
Category: Apache Cassandra
Category: Apache Kafka
Category: Software Design Patterns
Category: Data Architecture
Category: Database Management Systems
Category: Databases
Category: Apache Hive
Category: Data Management
Category: Cloud Computing
Category: Data Infrastructure
Category: Scalability
What you'll learn
Skills you'll gain
Category: Deep Learning
Category: Artificial Neural Networks
Category: Computer Vision
Category: Generative AI
Category: Keras (Neural Network Library)
Category: PyTorch (Machine Learning Library)
Category: Natural Language Processing
Category: Image Analysis
Category: Tensorflow
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Performance Tuning
Category: Network Architecture
Category: Machine Learning
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Build toward a degree
This Specialization is part of the following degree program(s) offered by Illinois Tech. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
Instructors
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Frequently asked questions
No, it’s not required—but it is recommended that you follow the course sequence listed on the specialization landing page. This order is designed to help you build your skills progressively, from foundational concepts to more advanced topics.
No, this specialization is open to all MOOC learners. You do not need to be an admitted degree-seeking student to complete the specialization and receive a Coursera–IIT co-branded non-credit certificate.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
More questions
Financial aid available,