Vaseem Durrani Data Scientist & Data Analyst
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Trained 10 thousand plus students over the past 12 years and transformed the career using a project-based learning approach. I Have implemented over 300+ research projects based on Artificial Intelligence and Machine Learning in Different domains.

I Work on innovative & challenging research/ business problems and solve them using Data Science, Machine Learning / Deep Learning. Always keen to learn new things in technology and implement the same in the application. and Love to share the knowledge with the students and make them understand the concept with project implementation. Provide assistance and support in the fields mentioned below

> Artificial Intelligence & Machine Learning Based solutions design
> Training professionals & students
> Exploratory Data Analysis using python | Power BI | Tableau
> Data Analytics and Visualization using Power BI | Tableau | SQL
> Computer Vision using Python OpenCV
> Prediction / Forecasting using Python | MATLAB
> Research paper implementation
> Optimization Algorithm application in different domains

My passion is sharing valuable knowledge and experiences to empower aspiring professionals in engineering and software development fields. I strive to make learning exciting while imparting career-enhancing practical skills

Subjects

Artificial Intelligence Deep Learning Beginner-Expert
Data Science and Machine Learning Beginner-Expert
Data analysis and visualization Beginner-Expert
Python 3 Beginner-Expert
Machine learning using MATLAB Beginner-Expert

Experience

Data Scientist (Sep, 2023–Present) at METAFISER TECH CONSULTING | DUBAI

● Offering AI and ML product consulting services to Clients.
● Providing customized solutions to clients based on their specific requirements.
● Ensuring timely delivery and implementation of projects.
● Developing and proposing new technical curriculums to align with current industry demands.
● Conducting train-the-trainer sessions to instruct trainers on effective training methodologies within the Metafiser
academy.
● Delivering training to Trainees on a variety of cloud-based AI and ML technologies.
Data Science Mentor (Jan, 2022–Jul, 2023) at LONDON INTERNATIONAL STUDIES & RESEARCH CENTER, DUBAI

> Delivering training to individuals interested in pursuing a career in Data Science, as well as to working professionals seeking to enhance their skills in the field.
> Ensuring that the training program is up-to-date with the latest industry standards and trends.
> Overseeing the delivery of the training program and managing project implementation
Data Analysis Researcher ML & Deep Learning (Jan, 2018–Dec, 2021) at Aedifico Tech Noida

> Facilitated Train the Trainer programs, ensuring curriculum alignment with the latest technology trends.
> Developed Machine Learning and Deep Learning research projects using Python.
> Deployed ML projects and implemented MLOps on AWS cloud infrastructure.
Sr. Researcher Python & MATLAB (Jan, 2014–Dec, 2017) at Aedifico Tech Pvt. Ltd. New Delhi, India

> Specialised project-based learning in Data analysis and machine learning domain.
> Executed various research projects for corporates using Python and data analysis libraries (Numpy,
Pandas, Matlplotlib, Seaborn).
> Providing training to college students in software development using Python and MATLAB
Researcher Embedded Systems (Jan, 2010–Dec, 2013) at Aedifico Tech Pvt. Ltd. New Delhi, India

> Implemented research projects in the embedded systems field for various clients.
> Designed and facilitated training programs for professionals and students on embedded systems and Embedded C.
> Delivered project-based learning sessions through short-term programs at universities and colleges.
Graduate Engineer trainee (Aug, 2007–Mar, 2009) at Schneider Electric, Chennai

Worked for Schneider Electric India Pvt. Ltd. as a Technical Automation Engineer
Technical Presentation & Demonstration of PLC, Drives, SCADA, Sensors and
Safety Products to clients Conducting Seminar on Sensor Safety products on client site
Providing Training on PLC, Drives, Sensors and Safety Products to the Schneider Electric Distributors and System Integrators

Education

Masters Software Systems (Jul, 2012–Apr, 2014) from Birla Institute of Technology and Science, Pilani, Pilani
Embedded Systemsand control (Mar, 2009–Sep, 2009) from CDAC NOIDA
B.Tech Electrical Engineering (Jun, 2003–Aug, 2007) from Jamia Millia Islamia, New Delhi

Fee details

د.إ71–142/hour (US$19.31–38.62/hour)

Fees may vary as per the needs and requirements

Courses offered

Python with Data Analysis
- د.إ2500
- Duration: 30 Hours
- Delivery mode: Online
- Group size: 2
- Instruction language: English
- Certificate provided: Yes
Python Introduction
- Introduction to Python
- Installing Python and IDEs
- Data Types (Numbers, Strings, Booleans)
- Variables and Assignments

Python Fundamentals
- Flow Control (if-else, for loops, while loops)
- String Manipulation
- User Input and Output

Python Data Structures
- Lists
- Tuples
- Dictionaries
- Sets

Python Functions and Modules
- Defining Functions
- Function Arguments and Return Values
- Built-in Functions
- Modules and Packages

Python Advanced Concepts
- List Comprehension
- Dictionary Comprehension
- Generators and Iterators
- Decorators

Introduction to NumPy
- NumPy Arrays
- Array Operations
- Broadcasting
- Indexing and Slicing

Data Analysis with NumPy
- Reading and Writing Data Files
- Array Manipulation
- Statistical Functions
- Linear Algebra Operations
- Case Study 1: Analyzing Stock Market Data

Introduction to Pandas
- Pandas Series and DataFrames
- Reading and Writing Data Files
- Data Cleaning and Preprocessing
- Handling Missing Data
- Case Study 2: Exploring COVID-19 Dataset

Data Analysis with Pandas
- Grouping and Aggregating Data
- Merging and Joining DataFrames
- Reshaping and Pivoting Data
- Time Series Analysis
- Case Study 3: Analyzing Sales Data

Data Visualization with Matplotlib and Seaborn
- Introduction to Matplotlib
- Line Plots, Scatter Plots, and Bar Plots
- Customizing Plots
- Introduction to Seaborn
- Seaborn Visualizations (Regression Plots, Heatmaps, etc.)
- Case Study 4: Visualizing Weather Data

Project 1: Building a Simple Data Analysis Dashboard
- Integrate Python, NumPy, Pandas, and Matplotlib/Seaborn
- Load and preprocess data
- Perform data analysis and visualizations
- Create an interactive dashboard using a Python library (e.g., Streamlit, Dash)

Project 2: Developing a Machine Learning Model
- Explore a dataset
- Preprocess and clean data
- Split data into training and testing sets
- Build and train a machine learning model (e.g., linear regression, decision trees)
- Evaluate model performance
Artificial Intelligence and Machine Learning using Python
- د.إ3000
- Duration: 40 Hours
- Delivery mode: Online
- Group size: 2
- Instruction language: English
- Certificate provided: Yes
Introduction to Machine Learning
- Overview of Machine Learning
- Supervised and Unsupervised Learning
- Python Libraries for Machine Learning (scikit-learn, NumPy, Pandas)
- Case Study: Predicting Housing Prices

Data Preprocessing and Feature Engineering
- Handling Missing Data
- Encoding Categorical Variables
- Feature Scaling
- Dimensionality Reduction Techniques (PCA, LDA)
- Case Study: Credit Card Fraud Detection

Linear Regression and Regularization
- Simple Linear Regression
- Multiple Linear Regression
- Polynomial Regression
- Regularization (Ridge, Lasso, Elastic Net)
- Project 1: Predicting Stock Prices

Classification Algorithms
- Logistic Regression
- K-Nearest Neighbors (KNN)
- Decision Trees and Random Forests
- Support Vector Machines (SVMs)
- Case Study: Loan Approval Prediction

Evaluation Metrics and Model Selection
- Confusion Matrix and Classification Metrics
- Cross-Validation Techniques
- Bias-Variance Tradeoff
- Hyperparameter Tuning
- Project 2: Spam Email Classification

Unsupervised Learning
- Clustering Algorithms (K-Means, DBSCAN, Hierarchical)
- Principal Component Analysis (PCA)
- Case Study: Customer Segmentation

Introduction to Deep Learning and Neural Networks
- Artificial Neural Networks (ANNs)
- Activation Functions
- Loss Functions and Optimization Algorithms
- TensorFlow and Keras Libraries
- Case Study: Handwritten Digit Recognition

Deep Learning for Computer Vision
- Convolutional Neural Networks (CNNs)
- Image Classification
- Object Detection and Localization
- Project 3: Image Classification (e.g., CIFAR-10 dataset)

Deep Learning for Natural Language Processing
- Recurrent Neural Networks (RNNs)
- Long Short-Term Memory (LSTM)
- Text Classification and Sentiment Analysis
- Case Study: Sentiment Analysis on Movie Reviews

Advanced Deep Learning Topics
- Autoencoders and Unsupervised Pretraining
- Generative Adversarial Networks (GANs)
- Reinforcement Learning
- Deploying Machine Learning Models
- Project 4: Reinforcement Learning for Game AI

The pre-requisite for this program is a basic fundamental understanding of Python programming