top of page

Our Core
Tech Offerings

BILTUP offers comprehensive support, tailored training, and customized training solutions for end users across the most popular technologies.

Untitled design (4).png

After connecting with many tech L&D leaders across the country, we’re seeing a fundamental shift in how developers want to learn and the need for tech L&D leaders to spearhead a paradigm shift.
Below are key areas we can support your team. Click on a topic for more information.

Software Engineering

Programming Languages

​​

  • Python

    • Core syntax, OOP, concurrency (asyncio, multiprocessing)

    • Web frameworks: Django, Flask, FastAPI

    • Data tools: Pandas, NumPy, Jupyter, PySpark

    • Dev tools: Poetry, Pipenv, Black, MyPy, Pydantic

  • JavaScript / TypeScript

    • ES6+ features, async programming, modules

    • TS deep dive: generics, decorators, type inference

    • Tooling: Vite, esbuild, TurboPack

  • Java

    • Core + JVM tuning

    • Spring Boot, Spring WebFlux, Spring Cloud

    • Jakarta EE, Micronaut, Quarkus

    • JUnit 5, Mockito, TestContainers

  • C# / .NET Core

    • ASP.NET Core, Blazor, Razor Pages, gRPC

    • LINQ, Entity Framework Core

    • MAUI, SignalR, Web APIs

    • Testing: xUnit, NUnit, Moq

  • Go (Golang)

    • Concurrency (goroutines, channels)

    • Web: Gin, Echo

    • gRPC, Protocol Buffers

    • Testing & benchmarking

  • Rust

    • Ownership, borrowing, lifetimes

    • Web frameworks: Actix, Rocket

    • Async with Tokio

    • Rust for systems, embedded, and performance-critical code

  • Other Languages (by demand)

    • Ruby (Rails), PHP (Laravel, Symfony), Scala, Kotlin, Swift, Dart (Flutter)

​

Modern Web Development

​​

  • Frontend Frameworks

    • React (Hooks, Suspense, Context, Server Components)

    • Angular (RxJS, NgRx, standalone components)

    • Vue (Composition API, Pinia, Vue Router)

    • Svelte, SolidJS, Alpine.js

  • Meta Frameworks

    • Next.js (App Router, server actions, middleware)

    • Nuxt 3 (Vue), Remix, Astro, Qwik, Eleventy

  • Architecture & APIs

    • RESTful API design (OpenAPI, Swagger)

    • GraphQL (Apollo, Relay, federation, caching)

    • tRPC, gRPC, WebSockets, SSE

  • UI/UX & Styling

    • TailwindCSS, CSS Modules, Styled Components

  • Accessibility (ARIA, WCAG)

  • ShadCN/UI, Radix UI, Chakra, Material UI

​

Testing & Quality

​​

  • Unit Testing (Jest, Pytest, JUnit, NUnit)

  • Integration & E2E Testing (Cypress, Playwright)

  • Test-Driven Development (TDD)

  • Behavior-Driven Development (BDD with Cucumber)

  • Mutation Testing

​

Software Design and Architecture

​​

  • Unit Testing (Jest, Pytest, JUnit, NUnit)

  • Integration & E2E Testing (Cypress, Playwright)

  • Test-Driven Development (TDD)

  • Behavior-Driven Development (BDD with Cucumber)

  • Mutation Testing

​

Secure Coding

​​

  • OWASP Top 10

  • Secure API development

  • Static/Dynamic analysis

DevOps & Infrastructure Engineering

​​

  • CI/CD: Jenkins, GitHub Actions, GitLab CI, CircleCI, Azure DevOps

  • Containers: Docker, Compose, Podman

  • Kubernetes:

    • Core concepts (Pods, Services, Deployments)

    • Helm, Kustomize

    • Advanced topics (RBAC, CRDs, Operators, Security)

    • K8s on AWS (EKS) / Azure (AKS)

  • Infrastructure as Code:

    • Terraform (core, modules, backends, workspaces)

    • Pulumi

    • Ansible

    • Bicep / ARM (for Azure)

  • Observability:

    • Prometheus, Grafana

    • Loki, Tempo, Jaeger

    • ELK Stack (Elasticsearch, Logstash, Kibana)

    • Fluentd, Datadog, New Relic

  • Secrets Management:

    • HashiCorp Vault

    • AWS Secrets Manager / Azure Key Vault

  • GitOps & Platform Engineering:

    • ArgoCD, Flux

    • Backstage (for internal developer portals)

Artificial Intelligence & Machine Learning

​​​

​Foundations

​​

  • Concepts

    • Regression, classification, clustering

    • Data cleaning, feature engineering, pipelines

  • Core Libraries & Tools: Scikit-learn, Pandas, NumPy, Matplotlib

​

Deep Learning

​​

  • Neural Network Architectures: ANN, CNN, RNN, LSTM, Transformers

  • Frameworks: PyTorch, TensorFlow, Keras

 

ML Ops and Deployment

​​

  • Model Serving:

    • Flask, FastAPI, TorchServe, TensorFlow Serving

  • ML Pipelines:

    • Kubeflow, MLflow, Apache Airflow

  • Operations:

    • Feature Stores (e.g., Feast)

    • Model Registry (e.g., MLflow, SageMaker Model Registry)

    • Model Monitoring & Drift Detection (e.g., Evidently, WhyLabs)

​

LLMs & Generative AI

​​

  • Foundational Topics:

    • Prompt Engineering

    • Tokenization, attention mechanisms, embeddings

    • Fine-tuning techniques (LoRA, PEFT)

  • Tools & APIs:

    • OpenAI GPT-4o, Azure OpenAI, Hugging Face Transformers & Inference API

    • LangChain, LlamaIndex

    • Vector databases: FAISS, Weaviate, Pinecone

  • Architectures:

    • Retrieval-Augmented Generation (RAG)

    • Function calling & agents (e.g., AutoGen, CrewAI)

​

Enterprise Use Cases

​​

  • AI-Assisted Development

    • GitHub Copilot (core usage, Copilot Labs, Enterprise integration)

    • Cursor (AI-native IDE workflows, context-rich agent interactions)

    • Best practices for secure AI coding

  • Process Automation

    • Document summarization, intelligent routing

    • Chatbots & virtual agents (Rasa, OpenAI Assistants API)

  • Other Applied Use Cases

    • Fraud detection

    • Demand forecasting

    • Knowledge retrieval

    • Forecasting & optimization in operations

Data Engineering & Analytics

​​

  • SQL Mastery: window functions, CTEs, indexing, performance tuning

  • ETL/ELT Pipelines:

    • Airflow, dbt, Fivetran

    • Stream Processing (Kafka, Flink, Spark Streaming)

  • Data Warehousing:

    • Snowflake, Redshift, BigQuery, Synapse

  • Data Lakes: AWS Lake Formation, Delta Lake

  • Data Modeling: Star, Snowflake schemas, data vault

  • Data Quality & Governance:

    • Great Expectations, OpenMetadata

    • Data contracts, lineage, versioning

  • BI Tools:

    • Power BI, Tableau, Looker

Cloud

Amazon Web Service (AWS)​

​​

  • Core Services: EC2, S3, IAM, VPC, CloudWatch, CloudTrail

  • Automation & Deployment: CloudFormation, CDK, CodePipeline, CodeDeploy

  • Serverless: Lambda, API Gateway, Step Functions, DynamoDB

  • Containers: ECS, EKS, Fargate

  • Networking: Route 53, ELB, NAT Gateway, Transit Gateway

  • Security: IAM Policies, KMS, GuardDuty, WAF

  • Data & Analytics: Redshift, Athena, Glue, QuickSight

  • DevOps on AWS: CI/CD, monitoring, cost optimization

  • AI/ML: SageMaker, Rekognition, Comprehend

​

Microsoft Azure

​​

  • Core Services: VMs, Blob Storage, Virtual Network, Azure Monitor

  • DevOps: Azure DevOps Pipelines, Repos, Artifacts

  • Containers & Kubernetes: AKS, Container Instances, Azure Container Registry

  • IaC: Bicep, ARM Templates, Terraform with Azure

  • Serverless: Azure Functions, Logic Apps, Event Grid

  • Identity & Security: Azure AD, RBAC, Key Vault

  • Data Stack: Synapse, Data Factory, Databricks, Cosmos DB

  • AI/ML: Azure ML, Cognitive Services

​

Google Cloud Platform (GCP)

​​

  • Compute & Storage: GCE, GCS, VPC

  • Containers: GKE

  • Data & AI: BigQuery, Dataflow, Vertex AI

  • IAM & Security

  • Cloud Build, Deployment Manager

Data Analysis and Business Intelligence

Foundations of Data Analysis

​​

  • Core Concepts

    • Descriptive & inferential statistics

    • Data wrangling & transformation

    • Exploratory data analysis (EDA)

    • Data storytelling & presentation best practices

  • Languages & Tooling

    • Python: Pandas, NumPy, Matplotlib, Seaborn, Plotly, Polars

    • SQL: Window functions, CTEs, joins, pivoting

    • R: tidyverse, ggplot2, dplyr, shiny (optional track)

 

​Business Intelligence Platforms

​​

  • Power BI

    • DAX language, Power Query

    • Data modeling (star schema, snowflake)

    • Dashboard and KPI report design

    • Row-level security & enterprise governance

  • Tableau

    • Tableau Desktop & Server

    • Data blending, LOD expressions

    • Interactive dashboards & storyboards

    • Tableau Prep for ETL workflows

  • Looker / Looker Studio (Google Data Studio)

    • LookML basics

    • Embedded analytics

    • Cross-platform data sources

  • Qlik Sense / QlikView

    • Associative data models

    • Expression editor, set analysis

 

​Data Integration & ETL/ELT

​​

  • ETL Tools

    • Apache Airflow, dbt, Fivetran

    • SQL-based ELT transformation workflows

    • Cloud-native tools: AWS Glue, Azure Data Factory, GCP Dataflow

  • Data Warehousing Concepts

    • OLAP vs OLTP

    • Star/snowflake schema

    • Time-series data and partitions

    • Data lakes and lakehouse architecture

​​

Advanced Topics

​​

  • Data Visualization Best Practices

    • Gestalt principles of design

    • Chart types (when to use what)

    • Cognitive load & dashboard UX

    • Interactive filters, drill-downs, tooltips

  • Data Governance & Compliance

    • GDPR, CCPA considerations

    • Data lineage & cataloging (e.g., Amundsen, DataHub)

    • Role-based access control

  • Metrics Engineering

    • Metric layers (Looker, dbt Semantic Layer)

    • Defining KPIs/OKRs

    • Building unified semantic models

​

Role-Based Focus Areas

​​

  • For Data Analysts:

    • Tableau/Power BI mastery, Excel integration, report automation, cross-functional storytelling

  • For Developers:

    • SQL + Python for data pipelines, embedding dashboards, API-driven BI integration

  • For Product & Growth Teams:

    • Product analytics (Amplitude, Mixpanel), funnel analysis, cohort analysis​

Security

Application Security

 

OWASP Top 10: modern threats & mitigations

  • Secure coding practices in:

    • Python

    • JavaScript/TypeScript (Node.js, React)

    • Java (Spring Security)

    • .NET (C#)

  • Input validation, encoding, and output escaping

  • Authentication & Authorization best practices

  • Secure session management

  • Secure API design (REST, GraphQL)

  • Dependency & package vulnerability scanning (Snyk, OWASP Dependency-Check, GitHub Dependabot)

 

Infrastructure & Cloud Security

  • Identity & Access Management (IAM)

    • AWS IAM Roles, Policies, SCPs

    • Azure RBAC and PIM

  • Network Security:

    • VPCs, subnets, NACLs, security groups

    • VPN, Bastion Hosts, Zero Trust Networking

  • Secrets Management:

    • HashiCorp Vault, AWS Secrets Manager, Azure Key Vault

  • Logging, monitoring, and alerting:

    • CloudTrail, GuardDuty, Security Hub

    • Azure Security Center, Defender

  • Encryption at rest and in transit (KMS, TLS, SSL, HSMs)

  • Secure containers & Kubernetes:

    • Pod security policies, network policies

    • Image scanning (Trivy, Clair, Anchore)

 

DevSecOps

  • Shift-left security mindset

  • Secure CI/CD pipelines:

    • Secrets detection in Git (Gitleaks, TruffleHog)

    • Code scanning tools (SonarQube, Semgrep)

    • SAST/DAST (Checkmarx, Veracode, ZAP)

    • Container scanning (Twistlock, Aqua)

  • Policy-as-code (OPA/Gatekeeper, Rego)

  • GitHub Actions security hardening

  • Software Supply Chain Security:

    • SBOM (Software Bill of Materials)

    • Sigstore & SLSA

  • Secure deployments using canary and blue/green

 

Identity, Access & Authentication

  • SSO (SAML, OIDC, OAuth2)

  • Federation with Azure AD, Okta, Auth0

  • MFA, adaptive authentication

  • Role- and attribute-based access control (RBAC/ABAC)

  • Just-in-time (JIT) access and audit logging

 

Security Governance, Risk & Compliance

  • Frameworks & standards:

    • NIST 800-53, NIST CSF

    • ISO/IEC 27001

    • SOC 2, PCI-DSS, HIPAA basics

  • Risk assessment workshops

  • Threat modeling (STRIDE, PASTA)

  • Security incident response planning

  • Building a security champions program

  • Internal audits & evidence gathering for compliance

 

Red Team / Blue Team Foundations 

  • Penetration testing basics

  • Recon & enumeration tools (Nmap, Burp Suite, Metasploit)

  • Simulated phishing & awareness training

  • MITRE ATT&CK mapping

  • Detection engineering

 

AI & LLM Security

  • Prompt injection and jailbreak risks

  • LLM data leakage concerns

  • RAG and vector DB threat models

  • AI code generation: bias, hallucination, license risk

​

​

Embrace the modern approach. Increase engagement, retention, and accelerate your workforce transformation.

bottom of page