Power BI Professional
Data Analytics 360 Professional
Machine Learning Engineer
Data Engineer
Full Stack Artificial Intelligence Developer
All CAIPi courses:
Are delivered online to allow you to learn from the comfort of your own home.
Are delivered live with hands-on training. Class recordings are available for reference.
Are taught by highly accomplished instructors from the Industry to teach and walk you through every step.
Industry capstone projects to simulate real work challenges and solution development steps.
Have global cohorts so you can network with students around the world.
Have Guest lectures from industry experts for mentoring and career development.
Are eligible for applying to exclusive Internship opportunities with CAIPi Partners.
Professional Development Hours: 23 hours
Content: In this course, you will learn how to perform data analysis using Excel and Power BI's most popular features. You will learn: Power Query, Data: Ingest, Transform, Visualization, Power Pivot: Creating Data Models, DAX Calculations, Time Intelligence, Publish Reports & Report Servers, Industry Use cases including Sales, HR, Retail, KPI & Business Insights Dashboards.
Learner Profile: Beginner, work as Power BI Developer, add new skill to existing role.
Professional Development Hours: 55 hours
Content: In this course, you will learn how to perform advanced end-to-end data analysis and prepares you for a career as an Analytics professional. You will learn:
Advanced Excel Module for analytics including storytelling through data visualization and dashboards, business automation through advanced formulae, pivot tables and macros.
Power BI Module including Power Query, Data: Ingest, Transform, Visualization, Power Pivot: Creating Data Models, DAX Calculations, Time Intelligence, Publish Reports & Report Servers.
SQL Module including Data Creation, Table Joins, Aggregation and Queries, Stored Procedure & Views, Data Improvements and Dat Cubes.
SQL Server Integration Service (SSIS) for Data Extract, Transform & Loading tool.
Machine Learning with Python & Statistics Module including complete Data operations and statistics using Python and Machine Learning Algorithms (LR, MLR, NLR, Clustering, Association Rule Mining, Classification, Feature Engineering & Ensembles methods).
Learner Profile: Beginner to Intermediate, career switch to Data Analytics roles.
Eligible for CAAI™ designation after completion.
Professional Development Hours: 80 hours
Complete Python programming, ML Probability & Statistics, Data Cleaning & Visualization in Python, complete Data operations and statistics using Python and Basic & Advanced Machine Learning Algorithms (LR, MLR, NLR, Clustering, Association Rule Mining, Classification, Feature Engineering & Ensembles methods), Feature Engineering and Cloud / ML Integration.
5 industry grade projects
Additional 20+ notebooks, 12 mini projects/code challenges with video.
Learner Profile: Intermediate, career switch to Advanced Analytics and Machine Learning Engineer roles.
Eligible for AIP™ designation after also completing Data Engineer Program.
Professional Development Hours: 40 hours
Data Engineering Introduction including ecosystem evolution and future roadmap.
Python for Data Engineering.
Relational Database Management System (RDBMS) including SQL, MySQL, SQLite, AWS Postgres fundamentals and queries.
NoSQL including NOSQL, MongoDB, Apache Cassandra and IBM Cloudant.
Big Data Engineering including Hadoop, Apache Spark, SparkSQL, ETL & ELT pipelines, Data and streaming pipelines using Airflow and Kafka.
Eligible for AIP™ designation after also completing Machine Learning Engineer Program.
Professional Development Hours: 12 hours
Eligible for Continuing Education credits for maintaining AIP™ designation.
