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ISTQB Agile Tester

Combine your testing knowledge with Agile methodologies in our ISTQB Agile Tester preparation course. Learn how to apply testing practices within Agile frameworks like Scrum and Kanban, collaborate with cross-functional teams, practice exploratory and session-based testing, and adapt your QA approach to fast-moving Agile delivery cycles.

Key Learning Outcomes:

• Understand Agile testing principles and how they differ from traditional testing approaches.
• Apply effective testing practices within Scrum, Kanban, and Agile delivery environments.
• Collaborate effectively with developers, Product Owners, and cross-functional Agile teams.
• Use exploratory and session-based testing techniques in fast-paced development cycles.
• Adapt QA strategies to support continuous delivery, rapid feedback, and high-quality software releases.

ISTQB Advanced Test Manager

This advanced course prepares experienced testing professionals for the ISTQB CTAL-TM certification — one of the most respected credentials in software testing. You’ll develop expertise in test management, organizational testing, risk-based testing, test process improvement, and defect management. Ideal for QA leads, test managers, and senior testing professionals.

Key Learning Outcomes:

• Develop advanced test management and leadership skills for complex testing projects.
• Apply risk-based testing strategies to identify and prioritize critical testing activities.
• Plan and manage test processes, resources, schedules, and deliverables effectively.
• Implement test process improvement and organizational testing practices.
• Strengthen defect management and decision-making skills for senior QA and test leadership roles.

Full Stack Developer

Our flagship Full Stack Developer program takes you from web fundamentals to advanced back-end development. Covering HTML, CSS, JavaScript, React, Node.js, Express, REST APIs, databases (SQL and NoSQL), and deployment practices, this course is designed for aspiring developers and career changers who want a comprehensive, job-ready skill set in modern web development.

Key Learning Outcomes:

• Master HTML, CSS, and JavaScript to build responsive and interactive web applications.
• Develop modern front-end applications using React and component-based development.
• Build scalable back-end applications with Node.js, Express, and REST APIs.
• Work with SQL and NoSQL databases for efficient data storage and management.
• Deploy and maintain job-ready full-stack web applications using modern development practices.

Agile AI Testing

Quality assurance is being transformed by AI. This pioneering course prepares QA professionals to test AI/ML systems within Agile environments — covering AI-assisted test generation, model validation techniques, bias and fairness testing, and the application of Agile testing principles in AI-native product teams. A vital course for testing professionals who want to remain relevant in the AI era.

Key Learning Outcomes:

• Understand AI/ML testing fundamentals and their application within Agile environments.
• Use AI-assisted tools and techniques to improve test case generation and test coverage.
• Apply model validation and performance testing techniques for AI/ML systems.
• Identify and test for AI bias, fairness, reliability, and potential risks.
• Integrate Agile testing practices into AI-native product development teams.

AI Full Stack Developer

Combine the power of full-stack development with AI integration skills in this comprehensive program. You’ll master both front-end and back-end development with modern frameworks (React, Node.js, Python), while also learning to integrate AI/ML models, build RAG pipelines, work with vector databases, and deploy AI-powered web applications. Perfect for developers who want to build the next generation of intelligent software products.

Key Learning Outcomes:

• Master full-stack development using modern technologies such as React, Node.js, and Python.
• Integrate AI/ML models into web applications and software products.
• Build Retrieval-Augmented Generation (RAG) pipelines for intelligent applications.
• Work with vector databases and AI-powered data retrieval techniques.
• Develop and deploy scalable, production-ready AI-powered web applications.

Agentic AI Development

The next frontier of AI is autonomous agents — systems that can reason, plan, and take actions without constant human input. This cutting-edge course teaches you how to design, build, and deploy agentic AI systems using frameworks like LangChain, AutoGen, and CrewAI. Learn to orchestrate multi-agent workflows, integrate external tools and APIs, and build AI agents that deliver real enterprise value.

Key Learning Outcomes:

• Understand the core concepts and architecture of Agentic AI and autonomous AI systems.
• Build intelligent AI agents using frameworks such as LangChain, AutoGen, and CrewAI.
• Design multi-agent workflows for complex problem-solving and task automation.
• Integrate external tools, APIs, and data sources into AI agent systems.
• Develop and deploy enterprise-ready AI agents that deliver measurable business value.

AI / ML Research & Development

Gain a deep understanding of machine learning algorithms, model development, training pipelines, and research methodologies with our AI/ML R&D course. From supervised and unsupervised learning to deep neural networks, natural language processing, and model evaluation, this course is designed for professionals who want to build and deploy production-grade ML systems.

Key Learning Outcomes:

• Understand core Machine Learning algorithms and model development techniques.
• Build and optimize supervised, unsupervised, and deep learning models.
• Develop efficient ML training pipelines for real-world applications.
• Apply NLP techniques and model evaluation methods to solve practical problems.
• Design and deploy production-ready AI/ML systems using industry best practices.

Life Sciences — Bioinformatics

Advance your expertise at the intersection of biology, data science, and technology. This program covers genomic data analysis, computational biology, and industry-standard tools (BLAST, NCBI, Python), along with essential research data management practices, including metadata standards, FAIR principles, reproducible workflows, and repository readiness.

Key Learning Outcomes:

• Understand bioinformatics fundamentals and the role of computational methods in modern life sciences.
• Analyze genomic and biological data using industry-standard tools such as BLAST, NCBI, and Python.
• Apply computational biology techniques to solve real-world research and biological data challenges.
• Implement metadata standards, FAIR principles, and reproducible workflows for research data.
• Prepare research datasets for effective management, sharing, and repository submission.

Leadership Management

Great technical skills get you in the room. Leadership skills keep you there. Our Leadership Management course develops the emotional intelligence, communication, strategic thinking, and team-building capabilities that transform individual contributors into respected leaders. Applicable across IT, data, Agile, and general management contexts.

Key Learning Outcomes:

• Develop effective leadership and communication skills to influence and inspire teams.
• Strengthen emotional intelligence for better relationships, decision-making, and conflict management.
• Apply strategic thinking and problem-solving to navigate complex business challenges.
• Build and lead high-performing, collaborative teams across different work environments.
• Develop the confidence to transition from an individual contributor to an effective leader.

CDMP Data Manager

Tezzonix offers a structured three-level pathway for data management professionals aligned with DAMA’s Certified Data Management Professional (CDMP) framework. Starting from Data Stewardship fundamentals (the foundation for data governance and quality), progressing through the Data Practitioner level (covering DMBOK knowledge domains in depth), to the advanced Data Manager level (strategic data leadership, architecture, and program management). Each course builds on the last, preparing you for your respective CDMP examination.

Key Learning Outcomes:

• Develop strategic data management leadership skills aligned with organizational goals.
• Design and oversee enterprise data governance, architecture, and management strategies.
• Lead data management programs, teams, and cross-functional initiatives effectively.
• Apply advanced practices for data quality, metadata, security, and data lifecycle management.
• Build the knowledge and confidence to prepare for the CDMP Data Manager examination.

CDMP Data Practitioner

Tezzonix offers a structured three-level pathway for data management professionals aligned with DAMA’s Certified Data Management Professional (CDMP) framework. Starting from Data Stewardship fundamentals (the foundation for data governance and quality), progressing through the Data Practitioner level (covering DMBOK knowledge domains in depth), to the advanced Data Manager level (strategic data leadership, architecture, and program management). Each course builds on the last, preparing you for your respective CDMP examination.

Key Learning Outcomes:

• Develop a strong understanding of core data management principles and DAMA-DMBOK knowledge domains.
• Apply best practices for data governance, data quality, metadata, and data architecture.
• Learn to manage data throughout its lifecycle and support effective organizational data practices.
• Analyze and address data management challenges using practical frameworks and approaches.
• Build confidence and knowledge to prepare for the CDMP Data Practitioner examination.

CDMP Data Stewardship

Tezzonix offers a structured three-level pathway for data management professionals aligned with DAMA’s Certified Data Management Professional (CDMP) framework. Starting from Data Stewardship fundamentals (the foundation for data governance and quality), progressing through the Data Practitioner level (covering DMBOK knowledge domains in depth), to the advanced Data Manager level (strategic data leadership, architecture, and program management). Each course builds on the last, preparing you for your respective CDMP examination.

Key Learning Outcomes:

• Understand the fundamentals of Data Stewardship, governance, and data quality.
• Apply data management best practices across key DAMA-DMBOK knowledge domains.
• Develop skills to improve data quality, ownership, accountability, and stewardship processes.
• Build effective data governance and management strategies within an organization.
• Prepare confidently for the CDMP examination through structured, progressive learning.

AI in Product Management

Artificial Intelligence is reshaping every product roadmap. This course teaches Product Managers and Product Owners how to integrate AI capabilities into their product strategy — from understanding AI/ML fundamentals to defining AI features, managing data requirements, and navigating the ethics of AI-powered products. A must-have course for any PM operating in a tech-forward environment.

Key Learning Outcomes:

• Understand AI and Machine Learning fundamentals and their application in product management.
• Identify and prioritize AI-powered product opportunities aligned with customer and business needs.
• Define AI features, data requirements, and product roadmaps effectively.
• Evaluate AI use cases, performance, feasibility, and business value.
• Navigate AI ethics, privacy, bias, and responsible AI practices in product development.

Professional Agile Leader (PAL)

Leadership in an Agile organization looks very different from traditional management. The PAL course helps leaders at every level understand Agile values, support self-organizing teams, adopt evidence-based management practices, and foster a culture of continuous improvement. Aligned with the Scrum.org PAL-E certification, this program is essential for managers, directors, and executives navigating Agile transformation.

Key Learning Outcomes:

• Understand the role of leadership in Agile organizations
• Create conditions for self-managing teams to succeed
• Support transparency, inspection, and adaptation
• Remove organizational impediments to agility
• Improve collaboration across teams and stakeholders
• Use evidence-based metrics to focus on value delivery

Professional Product Owner

Learn to maximize the value your team delivers with our Professional Product Owner course. You’ll develop expertise in backlog management, stakeholder communication, release planning, and product vision — all grounded in the Scrum framework. This course is ideal for aspiring Product Owners, Business Analysts, and Product Managers ready to step into a strategic Agile role.

Key Learning Outcomes:

• Understand the Product Owner’s role in Scrum
• Learn how to maximize product value
• Manage and refine the Product Backlog effectively
• Prioritize work based on customer and business value
• Collaborate with stakeholders and Scrum Teams
• Use empirical evidence to support product decisions

Professional Scrum Master

This intensive Scrum Master training equips you with the knowledge, mindset, and tools to lead Scrum teams effectively. You’ll explore the Scrum framework in depth — including Sprint Planning, Daily Scrum, Sprint Review, and Retrospectives — while building the servant leadership skills required to coach teams and remove impediments. This course directly prepares you for the Scrum.org PSM-I certification exam.

Key Learning Outcomes:

• Understand and apply the Scrum framework with fidelity
• Coach teams through Agile ceremonies and continuous improvement
• Navigate organizational impediments and stakeholder dynamics
• Prepare thoroughly for the Scrum.org PSM-I assessment

Manual Software Tester

Master the fundamentals of software quality assurance with our Manual Software Testing course. You’ll learn test planning, test case design, defect lifecycle management, and real-world testing techniques used by QA professionals worldwide. This course is the ideal starting point for anyone entering the software testing and quality assurance domain. Aligned with ISTQB CTFL concepts, it prepares you for both employment and certification.

Key Learning Outcomes:

• Understand the SDLC and STLC in depth
• Write effective test cases, test plans, and test reports
• Identify and log defects using industry-standard tools
• Apply black-box and white-box testing techniques
• Work confidently with test management tools like Jira and TestRail

Reproducible Analysis, Scientific Reporting and Portfolio Development

• End-to-end guided NGS project in your chosen domain
• Reproducible environment & workflow design guidance
• Full analysis pipeline support, start to finish
• Scientific report writing & data visualization coaching
• Final presentation & portfolio-ready project repository
• Project Completion Certificate
• 12–16 weeks of weekly 1:1 mentoring (18–24 hrs)

Somatic Variant Analysis and Biological Interpretation

• Cancer biology & sequencing strategies (tumor-normal design)
• Somatic variant calling & filtering
• Manual variant review in IGV
• Copy-number & structural variant concepts
• Cancer databases (COSMIC, ClinVar, OncoKB, CIViC)
• Driver prioritization & mutational signatures
• Certificate of Completion
• 12 live sessions, 1.5 hrs weekly

16S Amplicon Sequencing and Community Analysis

• 16S rRNA amplicon sequencing fundamentals
• Data processing with QIIME 2 / DADA2 concepts
• ASV/OTU generation & taxonomic classification
• Alpha and beta diversity analysis
• Community composition visualization
• Biological interpretation & reporting
• Certificate of Completion
• 10 live sessions, 1.5 hrs weekly

From Raw Reads to Differential Gene Expression

• RNA-seq experimental design & quality control
• Splice-aware alignment (STAR / HISAT2)
• Gene-level quantification & count matrices
• Differential expression analysis in R with DESeq2
• PCA, volcano plots & expression heatmaps
• Functional enrichment (Gene Ontology, pathway analysis)
• Certificate of Completion
• 10 live sessions, 1.5 hrs weekly

Alignment, BAM Processing and Variant Fundamentals

• Reference genomes & read alignment (BWA, Bowtie2)
• SAM/BAM processing with SAM tools
• Coverage & mapping-quality analysis
• Genome browsing & visual review in IGV
• Introductory variant calling and VCF interpretation
• Certificate of Completion
• 8 live sessions, 1.5 hrs weekly

Linux, FASTQ Quality Control and Read Processing

• Linux command-line fundamentals & file management
• Bash text processing (grep, awk, sed, sort, uniq)
• Downloading public sequencing data (SRA / ENA)
• FastQC & MultiQC quality assessment
• Adapter trimming and read filtering
• Reproducible project workflow & scripting
• Certificate of Completion
• 8 live sessions, 1.5 hrs weekly

Sequencing Technologies, Data Formats and Quality Concepts

• NGS platforms & sequencing technologies (Illumina, Nanopore, PacBio)
• Library preparation & sequencing workflow
• Core NGS file formats: FASTQ, SAM, BAM, VCF, BED, GFF/GTF
• Quality, depth & coverage concepts
• Public repositories & metadata (SRA, ENA, GEO)
• Certificate of Completion
• 6 live sessions, 1.5 hrs weekly

Sanger Sequencing, Quality Assessment and Sequence Preparation

• Hands-on training with real sequencing datasets
• Sanger sequencing fundamentals & chromatogram reading
• Phred quality scores and quality-region interpretation
• Sequence alignment and consensus building
• FASTA formatting and sequence preparation
• BLAST analysis and biological interpretation
• Certificate of Completion
• 4 live sessions, 1.5 hrs every Saturday