Our team of hand-picked data professionals are experts in data architecture, data engineering, data science, analytics, and full-stack development

Your path to becoming a data expert starts here

Welcome to Wise Academy, where we recognize that the true potential of data lies not just in its abundance but in the expertise to harness its power. At WiseAnalytics, we believe in investing in our greatest asset – our people. The Wise Academy is dedicated to training and nurturing employees into skilled data talents, empowering them to navigate the complexities of the digital landscape with confidence.
Additionally, we are committed to establishing Centers of Excellence for cutting-edge technologies like Databricks, ensuring our teams excel in the use of specific tools and platforms. Join us at Wise Academy as we embark on a journey to foster a culture of continuous learning, innovation, and excellence in the realm of data and technology. 

Data Engineering

Foundations of Big Data Processing with Apache Spark

Explore the fundamentals of Apache Spark, understanding its architecture, components, and applications in large-scale data processing. This course provides a solid foundation for harnessing the power of Spark in data engineering projects.

Real-time Data Streaming Mastery

Delve into real-time data streaming with a focus on the Apache Kafka ecosystem, KSQL, and practical applications of real-time streaming in data engineering. Participants gain hands-on experience in designing and implementing real-time data pipelines.

Advanced Streaming and Lakehouse Architecture

Elevate your data engineering skills with advanced topics, including Apache Spark Structured Streaming, Delta Tables, and the Lakehouse architecture. Gain insights into structured streaming, ACID transactions, and the integration of Delta Tables for effective data lake management.

Workflow Automation and Data Quality Control

Master workflow orchestration with Apache Airflow and optimize data processing using Python's Pandas library. Additionally, learn to ensure data quality and reliability with the Great Expectations framework. This comprehensive course covers DAGs, performance optimization, and robust data quality control practices.

Platform Engineering

Command Line Basics

In our 'Command Line Basics' course, participants will delve into the essential fundamentals of command line usage. This foundational module equips learners with the skills needed for efficient navigation, file manipulation, and task execution in various computing environments. From basic commands to advanced utilities, participants will gain a solid understanding of the command line, fostering proficiency in interacting with operating systems and executing essential tasks seamlessly.

Software Packaging

Our 'Software Packaging' course is designed to provide a comprehensive introduction to Python, focusing on setup and packaging essentials. Participants will explore the installation and configuration of Python environments, package management, and the fundamentals of Python scripting. This course is tailored to empower individuals with the necessary skills for effective Python application development, covering key concepts that form the backbone of scripting and software engineering in Python.

Infrastructure Foundations

Dive into the heart of modern infrastructure with our 'Infrastructure Foundations' course. Participants will explore core concepts, including operating systems, virtualization, and containers. Additionally, this course introduces the critical aspect of Infrastructure as Code (IaC) using Terraform. Learners will gain insights into managing and automating infrastructure deployment, ensuring scalability, efficiency, and consistency in infrastructure management.

Container Orchestration & CI/CD

The 'Container Orchestration & CI/CD' course is a comprehensive module covering advanced topics in infrastructure and software development. Participants will master the intricacies of containerization with Docker, delve into Kubernetes for container orchestration, and explore tools like Kaniko for building containers on Kubernetes. Additionally, the course introduces Gitlab CI fundamentals, emphasizing the importance of continuous integration and delivery in modern software development workflows. This course provides a holistic understanding of containerized environments and efficient software delivery pipelines.

Data Science & Software Engineering

Software Engineering for Data Professionals

This comprehensive course covers essential software engineering practices for both data engineers and data scientists. Explore key topics such as Algorithms & Data Structures, Testing Strategies, and Design Patterns tailored to meet the unique challenges of working with data-intensive applications. Gain proficiency in implementing robust, scalable, and efficient software solutions within the data science and engineering domains.

Introductory Data Science with Sklearn and XGBoost

Dive into the realm of advanced data science with a focus on the Scikit-learn library and XGBoost. This course provides an introduction to Sklearn, covering essential machine learning algorithms and techniques. Delve into boosting algorithms using XGBoost, gaining hands-on experience in building powerful predictive models. Elevate your data science skills with practical applications and real-world scenarios.

Data Science with Spark MLlib

Unlock the potential of distributed computing with our 'Data Science with Spark MLlib' course. Participants will gain proficiency in leveraging Apache Spark's MLlib for scalable and distributed machine learning. Explore various algorithms, model training, and optimization techniques specific to Spark MLlib, enhancing your ability to tackle large-scale data science challenges.

Holistic Data Science Mastery

This comprehensive course offering integrates key elements from both software engineering practices and data science domains. Participants will delve into Algorithms & Data Structures, Testing Strategies, and Design Patterns to fortify their software engineering skills. The data science component covers an introduction to Scikit-learn, boosting with XGBoost, and data science applications with Spark MLlib. This holistic mastery course provides a well-rounded education for professionals seeking expertise in both software engineering and data science.