Data Science and Machine Learning with Python Certification

Master Python to build real-world data pipelines

Open doors to in-demand data science and ML career roles

35 Hours | 14 Modules | Industry Simulations | Mini Projects

Earn a globally recognised certification

End-to-End Data Science & ML with Python and Power BI

4.8/5

3413 Enrolled

Overview

What our training includes:

Master Python programming fundamentals, including variables, functions, and data types across 14 structured modules
Develop strong data manipulation skills using libraries such as NumPy and Pandas
Perform data analysis and create insightful visualisations with Matplotlib and Seaborn
Apply machine learning techniques, including regression, decision trees, and clustering
Combine Python with Power BI to build interactive, data-driven dashboards with mini projects & industry simulations
Prepare learners for real-world Data Analyst and ML roles in this 35 hours training

Learning Outcomes

Upon finishing the training, you will:

Master Python programming with emphasis on data manipulation and analysis using NumPy and Pandas

Build and apply machine learning models, including regression, classification, decision trees and clustering techniques

Design clear and insightful data visualisations with Matplotlib and Seaborn to support business decisions

Gain hands-on experience with Power BI to create interactive and dynamic dashboards for real-world scenarios

Apply statistical techniques, hypothesis testing, A/B testing, and exploratory data analysis (EDA) to tackle practical business challenges

Conduct Exploratory Data Analysis (EDA), perform data cleaning and preprocessing using Python

Integrate ML outputs into business reporting systems

Ready to get started?

Overall ratings by our students

Upcoming sessions

Our Trainers

Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.

We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.

KHDA Certificate

Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.

Learners Point Certificate

Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.

Related courses

Curriculum

Python syntax, variables, data types
Conditional statements and loops
Functions and lambda functions
Lists, tuples, dictionaries, sets

Jupyter/Colab usage
NumPy arrays, indexing, reshaping
Vectorized operations
Numerical computation workflows

Load, clean, and merge data
Handling missing values
Filtering and slicing
Groupby operations

Mean, median, variance, standard deviation
Skewness and kurtosis
Probability rules and distributions
Business interpretation

Central Limit Theorem
Confidence intervals
t-tests, chi-square, ANOVA
Correlation vs causation

Histograms, bar plots, box plots
Heatmaps and correlation plots
Seaborn styling
Visualization best practices

Feature engineering
Scaling and encoding
Outlier treatment
Pattern identification
Data exploration workflows

Supervised vs unsupervised learning
ML workflow
Model evaluation metrics
Business applications

Linear regression
Logistic regression
Model evaluation
ROC-AUC and confusion matrix

Decision trees
Random forest
KNN algorithm
Model tuning
Predictive modeling

K-means clustering
Hierarchical clustering
PCA
Feature reduction
Segmentation models

Data integration
Power Query transformations
Visual dashboards
KPI tracking
Reporting workflows

Data modeling
DAX calculations
Multi-page dashboards
Forecasting models
Dashboard optimization

Export ML results
Dashboard integration
Predictive visualization
Data storytelling
Business intelligence workflows

Participants will build a fully functional data pipeline that collects, cleans, analyzes, visualizes, and models business data using Python and Power BI. This simulation integrates multiple data science concepts into an end-to-end solution aligned with real business scenarios.

The Automation Sandbox enables participants to apply the knowledge gained during the training to their own professional responsibilities and everyday work processes.
This activity encourages participants to examine their existing workflows and consider how the concepts learned in the program can be used to improve efficiency, streamline tasks, and support better operational outcomes.
Through guided exercises, participants will review and analyze their current workflows, identify opportunities for improvement through clearer structuring, simplification, and logical sequencing of tasks, and redesign processes using structured approaches.
They will translate their process expertise into well-defined workflow structures that outline key steps, decision points, and expected results.
These structured workflows are designed to be easily understood by technical automation teams, enabling effective implementation while bridging the gap between operational process knowledge and technical automation development.

Frequently asked questions

The Data Science and Machine Learning with Python Certification covers Python essentials, Jupyter/Colab, NumPy, Pandas, statistics, probability, hypothesis testing, EDA, and visualisation with Matplotlib and Seaborn. Participants practise cleaning, merging, analysing, and interpreting business datasets through guided activities and case studies.

It also covers machine learning models such as regression, classification, decision trees, random forests, KNN, clustering, and PCA. This course includes Power BI, DAX, forecasting dashboards, ML integration, an Industry Simulation, and an Automation Sandbox for workplace workflow improvement.

The Data Science and Machine Learning with Python Course helps participants turn raw data into practical business insight. It builds capability in Python, Pandas, NumPy, statistics, hypothesis testing, EDA, and visualisation with Matplotlib, Seaborn, and Power BI.

They also gain hands-on practice in machine learning, including regression, classification, clustering, and PCA. Through case studies, Industry Simulation, and the Automation Sandbox, they learn to build dashboards, analyse workflows, and support better decisions.

Prior coding experience is not mandatory for this course. This course begins with Python essentials, covering variables, data types, loops, functions, and core collections before moving into Jupyter, NumPy, and Pandas.

Participants with basic computer skills and analytical interest can follow the pathway gradually. This course then builds into statistics, EDA, machine learning, and Power BI, supported by guided exercises, case studies, Industry Simulation, and Automation Sandbox.

This program teaches tools used across data analysis, machine learning workflows, and business dashboarding. Participants practise them through guided exercises, case studies, and Power BI integration. The various tools included in this course are:

Python for data analysis and workflow automation
Jupyter/Colab for coding and notebook-based practice
NumPy for arrays and numerical computation
Pandas for cleaning, merging, and analysing data
Matplotlib and Seaborn for business data visualisation
Power BI, Power Query, and DAX for dashboards

Learners Point stands out as the premier destination for mastering Data Science and Machine Learning with Python. Offering a highly practical and industry-aligned approach to learning, here is why Learners Point is the best provider in the market to accelerate your career:

Expert-led instruction: Learn directly from seasoned instructors and industry professionals with exceptional credentials.
Practical curriculum: The course is designed to go beyond the basics, empowering you to truly master Python and build robust, real-world data pipelines from scratch.
Globally recognized certification: Upon successful completion, you earn a highly respected, globally recognized certification (and KHDA-approved institution).
Direct career advancement: The entire program is strategically crafted to open doors to highly lucrative and in-demand career roles in both Data Science and Machine Learning.
Maximum flexibility: Learners Point understands the needs of working professionals, offering highly flexible learning options tailored to fit busy schedules.
Proven track record of excellence: Boasting an exceptional 4.8/5 student satisfaction rating and over 3,400 successful enrollments in this course alone, the academy is a highly trusted and proven choice for professional upskilling.

Yes, this Data Science & ML program is beginner friendly because it starts with Python essentials, including variables, data types, loops, functions, and core collections. Participants then move into Jupyter/Colab, NumPy, Pandas, and data cleaning before handling statistics and visualisation.

The progression is practical-oriented. Participants build confidence through guided exercises, case studies, Industry Simulation, and Automation Sandbox before applying machine learning models such as regression, classification, clustering, and PCA.

Participants can apply their Python, statistics, machine learning, and Power BI skills across analytics, reporting, prediction, and business intelligence roles, depending on their experience level. The job roles are as follows:

Data Analyst
Business Intelligence Analyst
Junior Data Scientist
Machine Learning Associate
Reporting and Dashboard Analyst
Analytics Consultant

Yes, this training program is suitable for working professionals because it connects Python, statistics, machine learning, and Power BI with practical business tasks. Participants work through guided activities, case studies, and dashboard exercises that reflect analytics needs in reporting, forecasting, HR, finance, retail, and operations.

The Automation Sandbox makes it relevant for professionals. Participants examine current workflows, identify improvement areas, and structure processes for automation, while the Industry Simulation builds a complete data pipeline from cleaning to modelling and visualisation.

The Automation Sandbox is one of the most distinctive and career-defining components of this program. It is purpose-built to help you turn classroom learning into real workplace impact. The Automation Sandbox is integrated in the following way:

Apply learning to your own work: Rather than working on hypothetical scenarios, the Automation Sandbox gives you a dedicated space to bring your actual professional workflows into the learning environment.
Identify Automation opportunities: Through guided exercises, you learn to spot inefficiencies in your existing processes and evaluate where structured automation can drive measurable improvements.
Structure and simplify workflows: You learn to break down complex processes into clearly defined steps, decision points, and expected outcomes.
Bridge the gap between business and tech: One of the most valuable skills in any organisation is the ability to communicate process knowledge in a way that developers and data engineers can act on.
Suitable for all professional backgrounds: Whether you work in HR, finance, operations, marketing, or supply chain, the Automation Sandbox is designed to be relevant and immediately applicable.

This certification strengthens a software developer’s Python programming by moving beyond syntax into NumPy arrays, Pandas workflows, data cleaning, feature engineering, and vectorised computation. Participants practise writing code that prepares real business datasets for analysis and modelling.

It also adds practical machine learning programming skills, including regression, classification, decision trees, random forests, KNN, clustering, and PCA. Participants learn to evaluate models, interpret outputs, and connect results with Power BI dashboards.

Yes. This course builds dashboard skills gradually, starting with data visualisation using Matplotlib and Seaborn, then moving into Power BI, Power Query, and DAX. Participants practise creating visual reports, KPI views, and forecasting dashboards from cleaned business datasets.

They also learn to connect machine learning outputs with Power BI dashboards through predictive visualisation and data storytelling. Case studies include HR attrition, finance forecasting, and telecom churn, helping participants turn analysis into decisions.

This Data Science and Machine Learning with Python Training is unique through its clear shift from tool learning to business application. Participants work across Python, NumPy, Pandas, statistics, machine learning, and Power BI, then apply them through guided case studies in HR, finance, retail, loans, and telecom.

The real difference is the combination of Industry Simulation and Automation Sandbox. Participants build a complete data pipeline, integrate ML outputs into dashboards, and structure workplace workflows for automation-ready use.