Vessel Of Wisdom Academy

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Python Training classes

9

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Data Science Classes

9

Teaching Experience in detail in Data Science Classes

Artificial Intelligence & Machine Learning with Python Course Overview This course provides a structured and hands-on learning approach to Python, Machine Learning, Deep Learning, and Natural Language Processing (NLP), preparing participants for AI-driven careers. Designed for aspiring Data Scientists, Machine Learning Engineers, and AI Professionals, this program covers industry-relevant problem-solving techniques, real-world applications, and advanced AI/ML methodologies. By the end of the course, learners will be proficient in building AI/ML models and deploying them in practical scenarios. Trainer: Jaswant Kaur Total Course Duration: 45 Hours Course Breakdown (45 Hours) Module Duration Python for AI & ML 6 Hours Probability & Statistics for Machine Learning 4 Hours Data Preprocessing & Feature Engineering 5 Hours Exploratory Data Analysis (EDA) & Visualization 4 Hours Machine Learning Fundamentals 8 Hours Advanced Machine Learning Topics 4 Hours Time Series Forecasting 4 Hours Deep Learning & Neural Networks 5 Hours Model Deployment & MLOps 3 Hours End-to-End Project & Career Preparation 2 Hours

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in MySQL Certification Training

9

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Microsoft Power BI classes

9

Teaching Experience in detail in Microsoft Power BI classes

Power BI Training – Learn to Visualize & Analyze Data Effectively Master Power BI with easy-to-follow, practical training. Learn how to create dynamic dashboards, analyze data, and generate insights using real-world scenarios. This course includes: ✅ Live Online Classes with hands-on exercises ✅ Post-Class Notes & Interview Prep ✅ Regular Tests & Relentless Support Designed for beginners and professionals, this training will help you confidently use Power BI for data-driven decision-making.

Class Location

Online class via Zoom

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Tutor's Home

Years of Experience in IT Automation Infrastructure Automation

6

Teaching Experience in detail in IT Automation Infrastructure Automation

I have teaching experience in IT Automation with a strong focus on helping students understand how repetitive technical tasks can be automated using programming, scripting, and modern IT tools. My teaching approach is practical and project-based, where I explain concepts step by step and then demonstrate how automation is applied in real IT environments. I have taught learners how to automate routine tasks such as file handling, data processing, report generation, system monitoring, log analysis, email automation, and scheduled task execution. I also explain how automation improves efficiency, reduces manual errors, saves time, and supports scalable IT operations. In my sessions, I cover Python-based automation, including working with files and folders, using libraries, handling APIs, automating Excel or CSV tasks, web scraping basics, and writing scripts for repetitive workflows. I also introduce students to basic shell scripting, command-line usage, task scheduling, and automation logic used in real workplace scenarios. I focus on making students comfortable with the full automation workflow: identifying a repetitive task, breaking it into steps, writing automation logic, testing the script, handling errors, and improving the solution. I also teach debugging techniques so students can understand why an automation script fails and how to fix it. My teaching style includes real-world examples such as automatically organizing files, extracting information from documents, sending automated emails, generating daily reports, cleaning datasets, and monitoring system activities. These examples help students connect theory with practical IT automation use cases. I also guide students in building small automation projects that can be added to their portfolio. This helps them gain confidence and understand how automation skills are used in IT support, software development, DevOps, data operations, and business process automation. Overall, my IT Automation teaching experience is focused on practical learning, hands-on coding, real-world problem solving, and helping students become capable of creating automation solutions independently.

Class Location

Online class via Zoom

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Years of Experience in Tableau Training

10

Teaching Experience in detail in Tableau Training

I have teaching experience in Tableau with a focus on data visualization, dashboard creation, and business intelligence reporting. I train students to connect Tableau with data sources such as Excel, CSV files, Google Sheets, and databases. I explain important Tableau concepts such as dimensions, measures, filters, calculated fields, parameters, groups, sets, hierarchies, and dashboards. I teach students how to create different visualizations, including bar charts, line charts, pie charts, maps, heat maps, tree maps, scatter plots, dual-axis charts, and KPI cards. I also guide them on choosing the right chart based on the data and business requirement. My training is practical and project-based. I help students build dashboards related to sales analysis, customer analysis, HR analytics, finance reports, and marketing performance. I also teach formatting, dashboard layout, interactivity, action filters, drill-down analysis, and storytelling in Tableau. My goal is to help students gain confidence in Tableau, understand business data clearly, and create professional dashboards for academic projects, portfolio work, and data analyst roles.

Class Location

Online class via Zoom

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Years of Experience in AI Training

6

Teaching Experience in detail in AI Training

I have teaching experience in AI Training with a focus on helping students understand the fundamentals of Artificial Intelligence, Machine Learning, and practical AI tools. I explain AI concepts in a simple and structured way so that students can understand how AI systems learn from data and how they are used in real-world applications. In my AI training sessions, I teach important topics such as introduction to AI, machine learning basics, supervised learning, unsupervised learning, classification, regression, clustering, model training, model testing, accuracy evaluation, and basic data preprocessing. I also explain commonly used algorithms such as Linear Regression, Logistic Regression, Decision Trees, Random Forest, Naive Bayes, K-Means Clustering, and basic neural networks. I guide students in using Python for AI and machine learning. I train them on tools and libraries such as Jupyter Notebook, Google Colab, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, and basic TensorFlow or Keras concepts. I also teach how to load datasets, clean data, train models, evaluate results, and interpret model performance. My teaching approach is practical and project-based. I use real-world examples such as customer prediction, spam detection, sales forecasting, image classification basics, recommendation systems, chatbot basics, and sentiment analysis. These projects help students understand how AI is applied in business, education, healthcare, finance, and technology. I also introduce students to Generative AI concepts, including prompt writing, AI tools, chatbot usage, text generation, image generation concepts, and responsible AI practices. I help students understand how to use AI tools productively while also discussing accuracy, bias, privacy, and ethical usage. My goal is to make AI learning simple, practical, and career-oriented. I focus on building students’ confidence so they can understand AI concepts clearly, work on beginner-friendly AI projects, and prepare for academic, portfolio, and entry-level data science or AI-related opportunities.

Class Location

Online class via Zoom

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Years of Experience in Data Warehouse Training

6

Teaching Experience in detail in Data Warehouse Training

Here we are bribing Master Data Engineering with hands-on training in AWS, PySpark, Databricks, Snowflake, Airflow, ETL Pipelines, Data Warehousing, Lakehouse Architecture, Delta Lake, Spark Optimization, and Cloud Analytics. Learn through real-time projects, practical implementation, interview preparation, and placement guidance. Ideal for students and professionals targeting high-paying cloud and data careers.