Data Science and Machine Learning

This program is designed for professionals and aspiring Data Scientists, offering hands-on learning to build or enhance expertise in Data Science. Whether advancing your career, transitioning fields, or applying skills in your industry, it provides the tools and technical expertise employers highly value.

Start your journey to a global career in Data Science and Machine Learning! Gain hands-on skills and become an industry-ready professional

02 Months

Saturday, Sunday

3:00 - 5:00 PM PKT

04th January, 2025

Online & Interactive

English

Trusted by Leading Companies

Tools you will learn

Meet your Instructor

Sara Abbas is an experienced Machine Learning Engineer with over seven years of expertise in the corporate and academic sectors. She is dedicated to connecting industry knowledge with meaningful education to create impactful learning experiences.

Sara brings extensive industry experience, working with Data Science and AI teams to craft machine learning solutions for complex business challenges. She is passionate about empowering aspiring data professionals to bridge the gap between theory and real-world application through engaging, hands-on training sessions.

Who This Program is For?

Executives

Leaders who want to master data insights to drive smarter business decisions

Professionals

Those looking to level up their career with impactful data skills

Students

who want to get trained practically in Data Analytics with a complete industry-oriented approach

Data Enthusiasts

Individuals across industries like Supply Chain, Finance, Oil & Gas, Healthcare, and Sales who want to use data analytics to solve real-world challenges

What You’ll Learn

Module 1: Python for Data Science

– Intro to Python

– Variables, Data Types & Type Conversion in Python

– Numbers & Strings in Python

– Working with Lists in Python

– Conditionals & Loops in Python

– Functions & Built in Functions in Python

– NumPy in Python

– Dictionaries in Python

– Pandas Library in Python

– Manipulating Data Frames

– Data Visualization in Python (Matplotlib & Seaborn)

– Data Wrangling

– Data pre-processing and scaling

– Feature Extraction

Module 2: Descriptive statistics for Data Analysis

– Measures of central tendency

– Measure of dispersion

– Probability distribution

– Data visualization techniques & charts

Module 3: Exploratory Data Analysis & Model Preparation

– Data Pre-processing and scalling

– Data wrangling

– Feature extraction

– Splitting the dataset as per model requirement

Module 4: Time Series Analytics

– An introduction to time-series and stationary data

– Key concepts that include filters, signal transformations, and anomalies

– Spot trends, seasonality and secrets hidden in your data

– How to handle and visualize time series data

– Learn tricks to forecast what’s next.

– The application of time series forecasting with Python

Module 5: Machine Learning & Predictive Modelling

– K-nearest neighbors Naive Bayes

– Linear Regression

– Multivariable Regression

– Logistic Regression

– Decision Tree

– Support Vector Machine

– K-fold methods

– Model evaluation techniques

Module 6: Profile Building & Mentoring

– Career Prospects in Data Science, Data Analytics, Business Intelligence, and Analytical skills for Sales, marketing, Supply Chain, Finance and HR and other professionals

– Business case studies & capstone projects in each module

– Special guest sessions from Industry leaders from Amazon, Microsoft, Nike, Jazz and more.

– Cracking interviews with skills & tricks