Kuldeep Dhama

Years of Experience in Microsoft Power BI classes

20

Teaching Experience in detail in Microsoft Power BI classes

Microsoft Power BI – Teaching Experience I have conducted comprehensive training sessions in Microsoft Power BI, focusing on transforming professionals with little to no background in data analysis into confident Power BI users. My teaching approach emphasizes hands-on learning, real-time dashboards, and live project-based scenarios. Key Highlights: Taught Power BI to working professionals from domains like finance, marketing, operations, and IT support—most of whom were transitioning into data-driven roles. Structured my course to cover the complete BI workflow: data import, transformation using Power Query, DAX functions, data modeling, and building insightful reports and dashboards. Used real-time business use cases—including sales analytics, HR dashboards, and customer segmentation—for practical learning. Delivered live online sessions, supported by recordings, practice assignments, and quizzes. Familiarized learners with Power BI Desktop, Power BI Service, and Power BI Mobile, including how to publish and share dashboards. Provided continuous post-course support, resume tips, and interview preparation for BI/data analyst roles. Helped several students transition into data analytics roles using Power BI as their launchpad. Tools & Topics Covered: Power BI Desktop Power BI Service (cloud publishing and sharing) Power Query (M language basics) DAX (Data Analysis Expressions) Data modeling & relationships Visualizations & custom charts Row-level security Scheduled data refresh & gateways

Years of Experience in Python Training classes

10

Teaching Experience in detail in Python Training classes

I have extensive experience in teaching Python to a wide range of learners — from school students (10th–12th grade) to engineering students, working professionals, and corporate teams. Over the years, I have designed and delivered structured Python courses that focus not only on syntax but also on developing problem-solving skills through projects, real-world use cases, and algorithmic thinking. My teaching methodology emphasizes building strong fundamentals first (data types, control structures, functions, OOPs) and then moving into advanced areas (libraries like NumPy, Pandas, Matplotlib, Flask, Django basics, Data Science with Python). Key Highlights of my Python Training Experience: Level-wise Structured Courses: Beginner Level: Introduction to Python, basic programs, input/output, conditionals, loops, functions. Intermediate Level: Lists, tuples, dictionaries, sets, file handling, error handling, modules, libraries (NumPy, Pandas). Advanced Level: OOPs (Classes, Objects, Inheritance), Decorators, Generators, Lambda Functions, Database Integration, Web Development Basics (Flask). Special Focus: Data Analysis (Pandas), simple Machine Learning use cases (sklearn). Audience Taught: Students preparing for Engineering / University courses (taught Data Structures and Algorithms using Python). Working Professionals looking to switch to Data Science, AI/ML careers. Corporate batches for reskilling initiatives (Python for Automation, Data Handling, API integrations). Style of Delivery: Simple to Complex: I explain concepts in simple English, often using real-world analogies (example: explaining variables as "containers in your kitchen"). Step-by-Step Hands-on: Every concept is backed by live coding, quizzes, mini-projects, and assignments. Project-Oriented Learning: Created use cases like Student Database App, Employee Record Analyzer, Sales Dashboard using Python and Excel, Simple Web App in Flask, etc. Error Debugging Training: I train students to read errors, debug logically, and become independent coders. Teaching Modes: One-to-One Coaching (personalized attention, adaptive pace). Small Group Classes (3–10 participants for better interaction). Corporate Online Training (via Zoom, Teams, Google Meet). Tools and Techniques Used: Google Colab, Jupyter Notebooks, VS Code. Interactive Whiteboard teaching using diagrams (flowcharts, memory diagrams, call stacks). Assignment Systems: Weekly assignment submission and feedback cycle. Mock Interviews & Python coding tests for job readiness. Results Achieved: Students have successfully cracked internships, transitioned to Python-based roles, and started Data Science journeys. Several working professionals from non-programming backgrounds (like mechanical engineers, civil engineers) learned Python from me and shifted their careers toward analytics and automation. Unique Strengths: Patience and Adaptability: I adapt my speed and depth depending on whether the student is a school kid, college student, or a professional. Focus on Concept Mastery, not just Syntax: I encourage students to think like programmers rather than just memorize code. Real-world Use Cases: Teaching Python always connected to real-world tasks: file automation, data scraping, small apps, etc.

Years of Experience in Amazon Web Services Training

10

Teaching Experience in detail in Amazon Web Services Training

With a robust background in corporate IT and cloud infrastructure, I bring years of hands-on experience driving enterprise-level digital transformation using Amazon Web Services (AWS). My professional journey has been rooted in delivering scalable, secure, and cost-effective cloud solutions to Fortune 500 clients and fast-growing startups alike. My expertise spans architecture design, DevOps, security compliance, migration strategies, and performance optimization within AWS environments. Throughout my corporate career, I have consistently taken on mentoring and training roles, guiding cross-functional teams and upskilling internal staff in AWS technologies. Recognizing the growing demand for cloud fluency, I transitioned these efforts into structured teaching engagements. My teaching experience in AWS includes: Instructor-Led Training (ILT): Conducted both in-person and virtual sessions tailored for developers, system administrators, and solution architects. Courses covered core AWS services such as EC2, S3, IAM, RDS, Lambda, CloudFormation, and VPC, often culminating in certification readiness for exams like AWS Certified Solutions Architect – Associate and Professional levels. Customized Corporate Training Programs: Designed and delivered bespoke AWS workshops for organizations undergoing cloud adoption or migration. These sessions focused on real-world use cases, helping teams build practical skills aligned with their operational goals. Mentorship & Cloud Enablement: As a senior AWS practitioner within corporate settings, I led cloud centers of excellence and mentored internal staff. This included coaching junior engineers, guiding architecture reviews, and introducing best practices for cost optimization, security, and infrastructure as code using AWS-native tools like CDK and CloudFormation. Certification & Curriculum Development: Collaborated on the development of AWS-aligned learning paths and internal certification prep tracks. I’ve helped dozens of professionals successfully achieve AWS certifications by creating targeted study plans and mock assessments. My unique combination of deep AWS knowledge and real-world corporate insight allows me to bridge the gap between theory and practice, making my teaching highly relevant, engaging, and impactful.

Years of Experience in SQL Programming Training

13

Teaching Experience in detail in SQL Programming Training

SQL Programming Teaching Experience Over the past several years, I have developed and delivered comprehensive instruction in SQL programming to a wide range of learners, including university students, working professionals, and self-taught developers. My teaching methodology emphasizes hands-on learning, real-world problem solving, and progressive skill development. Course Development & Structure Beginner to Advanced Curriculum: I’ve designed structured learning paths, starting from foundational SQL topics (SELECT, WHERE, JOINs) to advanced queries (CTEs, Window Functions, Subqueries, and Stored Procedures). Interactive Labs: Each concept was reinforced with practical labs using real datasets (e.g., employee databases, ecommerce data, financial records). Project-Based Learning: Learners created end-to-end data analysis projects, including report generation and database schema design, simulating workplace tasks. Tools & Platforms Used Databases: MySQL, PostgreSQL, SQLite, SQL Server Environments: pgAdmin, MySQL Workbench, Azure Data Studio, DB Fiddle for browser-based practice Integration: Taught how SQL interacts with Python (using pandas and SQLAlchemy) and BI tools like Tableau and Power BI Instructional Approach Live Lectures & Workshops: Delivered step-by-step walkthroughs of query writing and optimization, with Q&A sessions and live debugging. Code Reviews & Feedback: Provided one-on-one support and feedback on query logic, efficiency, and formatting. Assessment: Developed quizzes, challenges, and capstone exams that focused on practical, job-relevant scenarios (e.g., writing queries for KPIs or cleaning inconsistent data). Special Focus Areas Performance Optimization: Taught how to analyze query plans, use indexes, and write efficient queries. Data Cleaning with SQL: Emphasized using SQL for wrangling messy data before analysis or modeling. Normalization & Schema Design: Explained the principles of relational database design and normalization techniques. Audience Undergraduate Students: For computer science and business analytics courses. Bootcamp Attendees: Accelerated learning for career changers and aspiring data analysts. Corporate Training: Customized SQL workshops for teams in finance, healthcare, and logistics. Outcomes Many learners successfully transitioned into data analyst, BI developer, and junior data engineer roles.

Years of Experience in Microsoft Azure Training

7

Teaching Experience in detail in Microsoft Azure Training

Microsoft Azure Training – Teaching Experience I have provided focused and structured Microsoft Azure training for engineering students, IT professionals, and corporate teams aiming to build or enhance their cloud computing skills, with a particular focus on Azure infrastructure, services, and DevOps integration. Course Development & Delivery Customized Learning Paths: Designed beginner to intermediate-level Azure courses aligned with specific roles like Azure Administrator, Azure Developer, and DevOps Engineer. Certification-Oriented Training: Provided targeted training for certifications such as: Microsoft Certified: Azure Fundamentals (AZ-900) Microsoft Certified: Azure Administrator Associate (AZ-104) Microsoft Certified: Azure DevOps Engineer Expert (AZ-400) Training Content & Focus Areas Core Azure Services Azure VMs, Storage Accounts, Resource Groups, Virtual Networks (VNets), Azure Load Balancer, and Azure App Services Identity & Access Management Azure Active Directory, RBAC (Role-Based Access Control), Policies ARM Templates & Bicep Infrastructure-as-Code basics and hands-on deployment practice Azure DevOps End-to-end DevOps pipeline setup using Azure Repos, Azure Pipelines, Boards, and Artifact management Monitoring & Security Azure Monitor, Log Analytics, Key Vault, Security Center, and Cost Management Hands-on Labs Real-world simulations in Azure portal & CLI: Deploying web apps, configuring load balancing, connecting VNets, automating infrastructure deployment with pipelines Tools & Platforms Used Azure Portal Azure CLI / PowerShell Visual Studio Code with Azure Extensions Azure DevOps Services GitHub Actions + Azure Integration Instruction Methodology Live Demonstrations: Every session included live portal walkthroughs and CLI-based hands-on configuration. Lab Assignments: Students completed lab exercises using free-tier or sponsored Azure credits to gain practical exposure. Project-Based Learning: Participants built mini-projects such as: Hosting a web application with CI/CD pipeline in Azure Setting up autoscaling for services based on metrics Implementing secure secret storage with Azure Key Vault Interactive Quizzes and Review Sessions: To reinforce learning and track progress toward certification readiness. Audience Engineering Students (Final Year & Pre-final Year): Focused on cloud fundamentals and project deployment. Corporate Teams: Delivered sessions for software development and IT support teams transitioning to Azure-based cloud architecture. Career Changers & Working Professionals: Provided crash courses and weekend workshops to help them switch roles into cloud-focused profiles.

Years of Experience in Snowflake Training

5

Teaching Experience in detail in Snowflake Training

I have conducted specialized training sessions in Snowflake – the cloud data platform – for both students and working professionals looking to build careers in cloud data warehousing, data analytics, and modern data architecture.

Years of Experience in BTech Tuition

20

Teaching Experience in detail in BTech Tuition

With 24 years of experience in the software industry, I have regularly visited universities in both India and the USA as a guest lecturer, teaching a variety of computer engineering subjects and sharing my industry knowledge with students

Years of Experience in Class 12 Tuition

15

Teaching Experience in detail in Class 12 Tuition

I have taught Mathematics to many Class 11 and 12 students over the years, and I’m proud to say that every one of them has shown significant improvement — not only in their board exams but also in competitive entrance exams like JEE Main, CUET, and others. Several of my students have scored 95% and above in their board exams, and many have secured excellent ranks in entrance tests. What sets my teaching apart is a clear focus on building strong fundamentals in each topic — whether it's Calculus, Algebra, Vectors, 3D Geometry, or Probability. I explain every concept in a way that connects with real problems, using step-by-step methods and plenty of practice questions that are aligned with both the board syllabus and entrance-level difficulty. I integrate regular problem-solving sessions, topic-wise mock tests, and shortcut techniques to improve speed and accuracy — all while making sure the student truly understands the logic behind the math. My students don’t just memorize formulas; they learn how and why the concepts work. Unlike many tutors who only focus on either boards or entrances, I prepare students for both, ensuring they’re confident in theory as well as problem-solving under time pressure. The goal is not just high marks, but long-term mathematical thinking and success in competitive exams. Every student I’ve taught has developed a stronger grasp of Maths, gained confidence, and started enjoying the subject — which reflects clearly in their results.

Years of Experience in Data Science Classes

10

Teaching Experience in detail in Data Science Classes

With over 24 years of professional experience in the IT industry and a strong academic background (B.E. in Computer Science, Executive Leadership from Harvard University), I bring deep, practical insights into Data Science and Machine Learning. I have trained engineering students, working professionals, and corporate teams across India, the USA, and the UK, offering real-world, hands-on training in Data Science using Python, SQL, Pandas, NumPy, Matplotlib, Scikit-learn, Power BI, and cloud tools like AWS and Azure. 🧑‍🏫 What I Teach in Data Science 🔹 Foundations: Python programming for data analysis Data structures and algorithms for data science Statistics & probability tailored for ML Linear algebra and calculus with practical interpretation 🔹 Data Handling and Processing: Data wrangling with Pandas and NumPy Real-world data cleaning, transformation, and encoding Exploratory Data Analysis (EDA) with Matplotlib & Seaborn Handling missing values, outliers, and categorical variables 🔹 Machine Learning: Supervised and unsupervised learning (regression, classification, clustering) Model evaluation (confusion matrix, ROC-AUC, cross-validation) Real-time use case modeling using Scikit-learn Feature selection and model tuning with GridSearchCV 🔹 Advanced: Time Series Forecasting (ARIMA, Prophet) NLP basics using NLTK and SpaCy Introduction to Deep Learning with TensorFlow/Keras Deployment of ML models using Flask/FastAPI My Teaching Approach Use-case first: Every module starts with a business scenario (e.g., fraud detection, medical diagnosis, churn prediction). Code + Concept: I explain line-by-line Python code and back it with intuitive theory. Assessment-focused: Weekly assignments, quizzes, and live projects to measure real progress. Interview prep: Regular mock interviews with scenario-based questions, model design, and optimization strategies. Audience I’ve Trained: Final year B.Tech students looking for data science careers Working professionals switching from Java/.NET to DS MBA graduates focusing on Business Analytics Corporate teams implementing end-to-end ML pipelines Tools & Platforms: Jupyter Notebook, Google Colab Power BI for dashboarding + data storytelling Git, VS Code, Postman AWS S3, EC2, SageMaker (intro level)