Data Science Training in Johannesburg

This instructor-led, live training in Johannesburg (online or onsite) is designed for beginner-level professionals who wish to grasp the concept of pre-trained models and learn how to apply them to solve real-world problems without having to build models from scratch.

By the end of this training, participants will be able to:

• Comprehend the concept and advantages of pre-trained models.
• Explore various pre-trained model architectures and their use cases.
• Fine-tune a pre-trained model for specific tasks.
• Implement pre-trained models in simple machine learning projects.

This instructor-led, live training in Johannesburg (online or onsite) is aimed at intermediate-level data scientists and analysts who wish to use AWS Cloud9 for streamlined data science workflows.

By the end of this training, participants will be able to:

• Set up a data science environment in AWS Cloud9.
• Perform data analysis using Python, R, and Jupyter Notebook in Cloud9.
• Integrate AWS Cloud9 with AWS data services like S3, RDS, and Redshift.
• Utilize AWS Cloud9 for machine learning model development and deployment.
• Optimize cloud-based workflows for data analysis and processing.

This instructor-led live training in Johannesburg (online or onsite) is aimed at intermediate-level participants who wish to automate and manage machine learning workflows, including model training, validation, and deployment using Apache Airflow.

By the end of this training, participants will be able to:

• Set up Apache Airflow for machine learning workflow orchestration.
• Automate data preprocessing, model training, and validation tasks.
• Integrate Airflow with machine learning frameworks and tools.
• Deploy machine learning models using automated pipelines.
• Monitor and optimize machine learning workflows in production.

This instructor-led, live training in Johannesburg (online or onsite) is designed to equip participants with the skills needed to prepare for the Microsoft Certified: Data Scientist Associate certification exam (DP-100).

The programme provides a comprehensive overview of data science and machine learning fundamentals, demonstrating how these concepts can be applied using Microsoft Azure Machine Learning. Participants will gain practical experience in preparing data, constructing and training machine learning models, and deploying these models to the cloud. Additionally, the course addresses techniques for evaluating model performance and executing feature engineering.

This instructor-led live training in Johannesburg (online or on-site) is aimed at beginner-level data scientists and IT professionals who wish to learn the basics of data science using Google Colab.

By the end of this training, participants will be able to:

• Set up and navigate Google Colab.
• Write and execute basic Python code.
• Import and handle datasets.
• Create visualizations using Python libraries.

Python has become increasingly popular within the financial sector, adopted by major investment banks and hedge funds to create a diverse array of financial applications, from core trading systems to risk management platforms.

In this instructor-led live training, participants will discover how to leverage Python to develop practical solutions for specific finance-related challenges.

Upon completion of this course, participants will be able to:

• Grasp the fundamentals of Python programming.
• Download, install, and manage the optimal development tools for building financial applications in Python.
• Select and employ the most appropriate Python packages and programming techniques to organise, visualise, and analyse financial data from various sources (such as CSV, Excel, databases, and web services).
• Develop applications that address issues related to asset allocation, risk analysis, investment performance, and more.
• Troubleshoot, integrate, deploy, and optimise a Python application.

Audience

• Developers
• Analysts
• Quants

Format of the course

• A blend of lectures, discussions, exercises, and extensive hands-on practice.

Note

• This training aims to provide solutions for some of the key problems faced by finance professionals. However, if you have a particular topic, tool, or technique that you wish to include or explore further, please contact us to arrange.

Explores practical methodologies for Data Science and AI utilizing Python, empowering professionals with the capabilities to analyse data, construct machine learning models, and implement AI-powered solutions within business environments; Addresses CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning via Tensorflow, natural language processing, big data processing with Spark, and data-driven storytelling; Perfect for novices pursuing a Python data science certification and comprehensive analytics training to enhance career prospects.

This is an ideal introduction to data science for managers, giving you the chance to learn about this powerful business tool.

KNIME Analytics Platform stands as a premier open-source solution for data-driven innovation, empowering you to uncover the latent potential within your data, extract fresh insights, or forecast future trends. Featuring over 1000 modules, hundreds of ready-to-run examples, a comprehensive suite of integrated tools, and the broadest selection of advanced algorithms, KNIME Analytics Platform serves as the ultimate toolbox for any data scientist or business analyst.

This course on KNIME Analytics Platform offers an ideal entry point for beginners, advanced users, and KNIME experts alike, introducing them to the platform, teaching them how to utilise it more effectively, and guiding them in creating clear, comprehensive reports based on KNIME workflows.

This instructor-led live training (available online or onsite) is designed for data professionals seeking to leverage KNIME to address complex business challenges.

The course targets individuals who may not have programming experience but wish to utilise cutting-edge tools to implement analytics scenarios.

By the conclusion of this training, participants will be able to:

• Install and configure KNIME.
• Build Data Science scenarios
• Train, test, and validate models
• Implement the end-to-end value chain of data science models

Format of the Course

• Interactive lecture and discussion.
• Ample exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request customized training for this course or to learn more about this programme, please contact us to arrange.

This instructor-led, live training in Johannesburg (online or onsite) is aimed at intermediate-level data analysts, developers, or aspiring data scientists who wish to apply machine learning techniques in Python to extract insights, make predictions, and automate data-driven decisions.

By the end of this course, participants will be able to:

• Understand and differentiate key machine learning paradigms.
• Explore data preprocessing techniques and model evaluation metrics.
• Apply machine learning algorithms to solve real-world data problems.
• Use Python libraries and Jupyter notebooks for hands-on development.
• Build models for prediction, classification, recommendation, and clustering.