ITCITEC
IT Excellence Circle LLP

Python for
Machine Learning

Practical AI & Machine Learning Program. Learn Python in the context of data, analysis and machine learning — live, structured and practical.

  • 8 Weeks
  • /Live Online
  • /32 Learning Hours
  • /Saturday + Sunday
  • /Google Meet

Launching Offer

PKR 15,000PKR 20,000

Limited to 30 seats • Orientation 7 September 2026

Enroll Now
View Course Details
ml_pipeline.ipynb
1import pandas as pd
2from sklearn.model_selection import train_test_split
3
4df = pd.read_csv("dataset.csv")
5df = df.dropna()
6X, y = df[features], df["target"]
7
8model.fit(X_train, y_train)
9preds = model.predict(X_test)
Python
Data
Model
Prediction
train → evaluatemodel output

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0

Live training hours

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Project hours

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Total learning hours

Positioning

Learn Python in the context of data and machine learning

This is not a standalone programming course. Python is introduced as the foundation for working with data, running analysis and building the groundwork for machine learning solutions — one continuous, practical pathway.

STEP 01

Python

Language foundations

STEP 02

Data Handling

Files, NumPy, Pandas

STEP 03

Data Analysis

Workflows & EDA

STEP 04

Visualization

Matplotlib

STEP 05

Machine Learning

Foundations

STEP 06

Practical Projects

Applied work

Why Python

Why Python for machine learning?

Python sits at the centre of most modern data and machine learning workflows. Here is what that means in practice for a learner.

01

The working language of data

Python is widely used across data processing, analysis and machine learning workflows, which keeps one language relevant from raw files to model output.

02

A mature library ecosystem

NumPy, Pandas and Matplotlib cover numerical work, tabular data and visualization, so learners spend time on problems rather than infrastructure.

03

Readable, practical syntax

Clear syntax makes analysis code easier to write, review and maintain — an advantage when working with datasets in teams.

04

Industry relevance

Python is commonly used in analytics, automation, research and applied AI work, making it a practical foundation for continued learning.

The program builds practical skills. It does not promise employment or claim to make anyone an AI engineer in 8 weeks.

Curriculum

What you will learn

Four confirmed modules delivered across eight weeks, each one building directly on the previous.

01

Weeks 1–2

Python Foundations

Core language fundamentals with continuous hands-on practice.

02

Weeks 3–4

Data Handling with Python

Moving from language basics to working with real data structures and files.

03

Weeks 5–6

Data Analysis & EDA

Structured analysis workflows on real datasets.

04

Weeks 7–8

Data Visualization

Communicating findings clearly, alongside project work.

  • Introduction to Python
  • Why Python
  • Installing Python
  • Python IDEs
  • Python syntax
  • Variables
  • Data types
  • Operators
  • Python built-in functions
  • Conditional statements
  • Looping statements
  • Lists
  • Tuples
  • Sets
  • Dictionaries
  • Comprehensions
  • Error handling
  • Practical exercises
  • Real-world problem solving using Python

Tools & Skills

The stack you will work in

A focused toolset, used consistently throughout the program.

TOOL

Python

Core language

TOOL

Jupyter Notebook

Interactive analysis

TOOL

Anaconda

Environment & packages

Python ProgrammingNumPyPandasData CleaningData AnalysisExploratory Data AnalysisData VisualizationMachine Learning foundationsPractical problem solving

Practical Learning

Learn by working with data

Sessions are built around doing the work: writing Python, cleaning datasets, running analysis and producing visual output — not only watching lectures.

01

Understand

Concepts explained live with worked examples.

02

Practice

Hands-on Python exercises in every session.

03

Analyze

Data cleaning and EDA on real-world datasets.

04

Visualize

Communicate findings with clear plots.

05

Build

Project work applying the full workflow.

Work includes hands-on Python exercises, dataset analysis, data cleaning, EDA, visualization and practical machine learning work through project-based learning. Specific project topics are finalized by the instructor based on the cohort.

Instructor

Who teaches the program

Sessions are delivered live by an ITEC instructor. Full instructor details will be published once confirmed by ITEC.

ITEC

Instructor NamePlaceholder

Instructor profile, professional background and experience will be added here once ITEC provides the final details.

Teaching approach

  • Live explanation of every concept, followed by hands-on practice.
  • Work on real-world datasets rather than toy examples only.
  • Questions answered during the session, in context.
  • Structured progression — each module builds on the previous one.

Career relevance

Where these skills are applied

The program builds practical, transferable skills. It does not guarantee employment — the paths below describe where Python, data analysis and ML foundations are commonly used.

Data Analyst

Cleaning, analysing and reporting on datasets using Python, Pandas and visualization.

Python Developer (Data focus)

Writing practical Python for data processing, automation and analysis workflows.

Junior Data Scientist

Building on EDA, preprocessing and machine learning foundations covered in the program.

AI / ML Learner Track

A structured base for continued study in machine learning and applied AI.

01Python skills are in demand across analytics, automation and research roles.
02Data handling and EDA are everyday tasks in most data-facing positions.
03Visualization turns analysis into decisions stakeholders can act on.
04Project work gives you something concrete to show and discuss.

Program details

Schedule, format and requirements

Everything confirmed by ITEC about how the program runs.

Format
Live Online Training
Platform
Google Meet
Duration
8 Weeks
Class days
Saturday + Sunday
Session length
2 Hours
Live training hours
24 hours
Project hours
8 hours
Total learning hours
32 hours
Orientation
7 September 2026
Regular classes begin
12 September 2026
Seats
30 seats
Recordings
Not provided — live participation

Who should join

  • Students
  • Fresh graduates
  • Working professionals
  • Career switchers
  • Developers with basic programming knowledge

Basic programming knowledge is required. Advanced Python or machine learning experience is not.

Certificate

ITEC Certificate of Completion

Participants who meet ITEC's completion requirements will receive the relevant ITEC certificate.

Certificate preview

Placeholder — certificate design will be added once provided by ITEC.

Enrollment

How to enroll

Three steps. Seats are limited to 30 for this cohort.

STEP 01

Submit the enrollment form

Complete the ITEC Google Form with your details.

STEP 02

Complete the fee payment

Payment details placeholder — bank / payment instructions will be added once provided by ITEC.

STEP 03

Receive confirmation

ITEC confirms your seat and shares the Google Meet joining details before orientation.

Enroll NowQuestions? Email info@itexcellencecircle.site

Pricing

One program, one fee

A launching offer is available for this cohort. No hidden charges.

Launching offer

PKR 15,000PKR 20,000

Limited to 30 seats for this cohort.

Enroll Now

Payment instructions placeholder — will be added once provided by ITEC.

What's included

  • 24 live online training hours
  • 8 dedicated project hours
  • Hands-on exercises in every session
  • Real-world dataset analysis
  • Live Q&A during sessions
  • ITEC certificate on completion requirements

Orientation

7 September 2026

Classes begin

12 September 2026

Seats

30

FAQ

Frequently asked questions

Everything ITEC has confirmed about this cohort.

Enrollment open

Start with Python. Build towards machine learning.

8 Weeks live online, 32 learning hours, 30 seats. Orientation on 7 September 2026.

Enroll NowPKR 15,000 launching offer • was PKR 20,000

PKR 15,000

was PKR 20,000 • 30 seats

Enroll Now