Course DescriptionArtificial Intelligence (AI) and Big Data have come together to drive innovation in 2018 and 2019. AI works to light up Big Data. This combination elevates the potential for you to realize significant insights into customers, trends, and products in your domain. Big Data without analysis and tools that can navigate the petabytes of data, is much about nothing. This collectively is the art and science of Data Analytics. This includes general users, the dedicated Project Manager and Business Analyst role, and the specialized Data Scientist roles.
This course explores the value that is in the intersection of Big Data and AI as practiced with Data Analytics. We will look at the potential and the dangers that exist. We will also view the trends of Big Data and AI, providing a pragmatic and applicable survey of the technologies and the business applications.
Course Objectives- Evaluate what is realized, what is promised and what are the challenges of Big Data
- Establish a plan allowing you to get the most out of a Big Data and AI using a Data Analytics initiative
- Review the architecture and technical components of Big Data and Data Analytics
- Investigate Data Mining and other applications for Big Data and Data Analytics
Course TopicsIntroduction to Data analysis and analytics
- Data analysis approach
- Questions
- Collecting data
- Analyze data
- The data analysis process
- Interpreting the results
- Statistics
- Rules for data analysts
Big Data- Business challenges of Big Data
- Technical challenges of Big Data
- Common uses for Big Data
- Structured, Semi-structured and Unstructured Data
- Transform data into value for the business
- Working with Big Data
- Locating
- Extracting
- Processing
- Storage
- Analysis
- Representation
- Identifying data sources
- Applying Big Data to business problems
Interpreting the Big Data- Guarding against bias
- Conclusions
- Conclusion validity
- Internal validity
- Construct validity
- External validity or generalizing
Data Visualization- Plots and charts
- Aggregation
- Scaling
- Normalizing data
- Dimension reduction
- Correlation
Applying analytics- Classification
- Business examples for Data Mining – classification
- Predictive Analytics
- Business examples for Data Mining - prediction
- Clustering
- Neural networks
Artificial Intelligence- Artificial Intelligence Introduction Course for Beginners
- Artificial Intelligence Introduction
- Decoding AI, what is it all about?
- Use cases in various industries
- Introduction to Machine Learning (ML) and Deep Learning
- Innovations in AI and ML
- Applications of AI
- How to develop AI products
Final Words- Artificial intelligence
- Where are we now
- Where are we going to be
- Making things happen with data analytics and big data
