This machine learning course introduces the methods used to build systems that learn from data and make informed predictions. Explore supervised and unsupervised learning, data preparation, feature engineering, model evaluation, classification, regression, clustering, and practical model selection. The course focuses on understanding how algorithms identify patterns, measure performance, and support applications such as forecasting, recommendation engines, and anomaly detection.
Enrolled Agent Certification preparation focuses on the knowledge tested in the IRS Enrolled Agent exam and the responsibilities of federally authorized tax practitioners. Explore individual and business taxation, representation procedures, taxpayer rights, ethics, and IRS processes. This tax professional training helps learners build a structured understanding of tax rules and the practical issues involved in preparing returns and representing taxpayers before the IRS.
Natural Language Processing explores how machines analyse, interpret, and generate human language using Python and machine learning. The course examines essential NLP workflows, from text cleaning, tokenisation, and feature extraction to sentiment analysis, text classification, named entity recognition, and language-model applications. It is designed for learners who want to work with real-world text data and build intelligent systems for search, chatbots, document analysis, and automated language tasks.
This marketing analytics training explores how Python can turn campaign, customer, and channel data into practical marketing insight. Learn to work with marketing datasets, analyse performance metrics, segment audiences, visualise results, and support data-driven marketing decisions. The course connects Python-based analysis with everyday marketing questions, from measuring campaign outcomes to identifying patterns that inform targeting and budget choices.
Machine Learning With R explores how R programming supports data science workflows, from preparing datasets and selecting features to building and evaluating predictive models. The course focuses on applying R’s statistical and visualization capabilities to classification, regression, clustering, and model assessment, helping learners interpret results and make evidence-based decisions from data.
Bitcoin Training examines how the Bitcoin network records ownership, validates transactions, and operates without a central authority. Explore wallets, private keys, addresses, blockchain structure, consensus mechanisms, Bitcoin mining, transaction fees, and common security practices. The course also places Bitcoin within digital finance, helping learners understand its practical use, network economics, and relationship to wider cryptocurrency and blockchain development concepts.
Python Data Analytics training examines how Python turns raw datasets into useful business evidence. The course focuses on data cleaning, exploratory analysis, transformation, and data visualization, using Python workflows to identify patterns, measure performance, and communicate findings clearly. Learners work with the analytical techniques behind data-driven decision-making, building practical confidence in preparing data and presenting results for real operational questions.
Python Django training explores how to create secure, maintainable web applications with Django’s Python framework. The course focuses on project structure, URL routing, views, templates, models, database operations, forms, user authentication, and the Django admin interface. Learn Django online through practical application development patterns, from handling requests and organising reusable apps to working with relational data and deploying well-structured web projects.
Python Game Development training focuses on building playable 2D games with Python and Pygame. Explore the core mechanics behind game loops, player movement, keyboard input, collision detection, sprites, scoring, sound, and screen updates. The course connects Python programming concepts with the practical structure needed to create interactive games, from setting up a window to managing gameplay events and game states.
Python Software Development Training introduces the programming practices used to build, test, and maintain Python applications. It explores writing readable Python code, structuring programs into reusable components, working with data and errors, and applying core software-development principles. This course provides a focused foundation in Python programming for creating reliable scripts, tools, and application features.
Machine learning training examines how intelligent systems learn from data to make predictions, recognise patterns, and support automated decisions. The course introduces core artificial intelligence concepts alongside supervised and unsupervised learning, deep learning models, and natural language processing. Learners explore the workflows behind preparing data, building models, evaluating performance, and applying AI methods to practical analytical problems.
Artificial Intelligence and Machine Learning with Python Training introduces the Python-based methods used to build intelligent, data-driven applications. The course explores data preparation, supervised and unsupervised learning, model evaluation, and core AI concepts through practical Python workflows. Learners work with algorithms for prediction, classification, clustering, and pattern recognition while understanding how machine learning models are developed and applied.
The ZebLearn Implementing Power Infrastructure for Cloud Training delivers expert skills in designing, deploying, and managing high-reliability power systems for cloud data centers and hyperscale facilities. Master UPS systems sizing, PDU deployment, generator backup strategies, power distribution units (PDU), DC power architectures, power usage effectiveness (PUE) optimization, and liquid cooling power integration for high-density cloud computing. Learn advanced power infrastructure implementation including Tier III/IV redundancy design, power monitoring with DCIM tools, CRAC/CRAH cooling integration, battery backup systems (VRLA/Lithium-ion), ATS transfer switches, power quality analysis, and renewable energy integration (solar/wind hybrid). Implement fault-tolerant architectures, capacity forecasting, power density planning for AI/ML...
The IBM Spectrum Protect Implementation and Administration Training from ZebLearn provides hands-on expertise in deploying, configuring, and managing IBM Spectrum Protect (formerly Tivoli Storage Manager) for enterprise data protection across servers, VMs, and cloud.Acquire skills in server installation, client setup, policy management, storage pools/deduplication, replication/disaster recovery, node/client operations, reporting/monitoring, and performance tuning for scalable backup solutions.Essential for storage admins, backup engineers, and IT ops teams handling data retention, ransomware protection, and business continuity in hybrid environments.
The IBM Storwize V7000 Implementation Training from ZebLearn equips you with skills to deploy and configure IBM Storwize V7000 unified storage arrays for virtualization, performance optimization, and data management.Hands-on coverage includes enclosure setup, RAID arrays, storage pools creation, host mapping, thin provisioning, Easy Tier tiering, FlashCopy replication, SVC-style clustering, iSCSI/Fibre Channel connectivity, and GUI/CLI management.Targeted at storage engineers, SAN admins, and IT architects planning hybrid flash deployments for virtualization, databases, and mission-critical workloads.
The IBM DS8000 Implementation for Open Systems Training at ZebLearn provides in-depth guidance on deploying IBM DS8000 enterprise disk systems for Linux, Windows, AIX, and other open platforms using FICON/Fibre Channel connectivity.Cover initial setup with DS CLI and Storage Manager GUI, array/rank/extent pool configuration, fixed-block (FB) volume creation, host attachment with WWPN mapping, performance optimization via Easy Tier, Copy Services like FlashCopy/Global Mirror, and monitoring for high-availability storage.Designed for storage specialists, system engineers, and data center admins responsible for mission-critical open systems environments demanding sub-millisecond response times and robust DR capabilities.