Data Science and Machine Learning with Python Certification in Saudi Arabia

Upcoming sessions

Curriculum

1

Python syntax, variables, data types

2

Conditional statements and loops

3

Functions and lambda functions

4

Lists, tuples, dictionaries, sets

1

Jupyter/Colab usage

2

NumPy arrays, indexing, reshaping

3

Vectorized operations

4

Numerical computation workflows

1

Load, clean, and merge data

2

Handling missing values

3

Filtering and slicing

4

Groupby operations

1

Mean, median, variance, standard deviation

2

Skewness and kurtosis

3

Probability rules and distributions

4

Business interpretation

1

Central Limit Theorem

2

Confidence intervals

3

t-tests, chi-square, ANOVA

4

Correlation vs causation

1

Histograms, bar plots, box plots

2

Heatmaps and correlation plots

3

Seaborn styling

4

Visualization best practices

1

Feature engineering

2

Scaling and encoding

3

Outlier treatment

4

Pattern identification

5

Data exploration workflows

1

Supervised vs unsupervised learning

2

ML workflow

3

Model evaluation metrics

4

Business applications

1

Linear regression

2

Logistic regression

3

Model evaluation

4

ROC-AUC and confusion matrix

1

Decision trees

2

Random forest

3

KNN algorithm

4

Model tuning

5

Predictive modeling

1

K-means clustering

2

Hierarchical clustering

3

PCA

4

Feature reduction

5

Segmentation models

1

Data integration

2

Power Query transformations

3

Visual dashboards

4

KPI tracking

5

Reporting workflows

1

Data modeling

2

DAX calculations

3

Multi-page dashboards

4

Forecasting models

5

Dashboard optimization

1

Export ML results

2

Dashboard integration

3

Predictive visualization

4

Data storytelling

5

Business intelligence workflows

1

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.

1

The Automation Sandbox enables participants to apply the knowledge gained during the training to their own professional responsibilities and everyday work processes.

2

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.

3

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.

4

They will translate their process expertise into well-defined workflow structures that outline key steps, decision points, and expected results.

5

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.

Meet your Trainer

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.

Our Trainers

Learning Outcomes

Upon finishing the training, you will:

1

Master Python programming, focusing on data manipulation using NumPy and Pandas

2

Develop and implement machine learning models such as regression, classification, decision trees, and clustering

3

Create insightful data visualizations with Matplotlib and Seaborn for actionable business decisions

4

Gain practical experience in Power BI to build interactive and dynamic data dashboards

5

Apply hypothesis testing, A/B testing, and exploratory data analysis (EDA) to solve real-world business problems

6

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

7

Integrate ML outputs into business reporting systems

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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.

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Learners Point Certificate

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

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Frequently asked questions

The Data Science and Machine Learning with Python Certification in Saudi Arabia teaches participants how to work with business data using Python, Jupyter/Colab, NumPy, and Pandas. They learn data cleaning, merging, statistical analysis, probability, hypothesis testing, EDA, and visualisation with Matplotlib and Seaborn.

It also builds practical machine learning capability through regression, classification, decision tree, random forests, KNN, clustering, and PCA. Participants then connect model outputs with Power BI dashboards, forecasting views, KPI tracking, and business intelligence workflows.

The Data Science and Machine Learning with Python Course in Riyadh builds analytics workflow skills by taking Participants through the full data cycle. They start with Python essentials, Jupyter/Colab, NumPy, and Pandas, then practise cleaning, merging, filtering, and analysing business datasets.

Participants then move into statistics, EDA, machine learning models, and Power BI dashboards. This course connects these stages through case studies and an Industry Simulation, where Participants build a complete pipeline from data collection to visual insight.

Participants work on practical business cases that connect Python, statistics, machine learning, and Power BI with reporting, prediction, segmentation, and dashboard development. These are the practical projects included in this course:

Retail and HR dataset analysis
Business hypothesis testing and feature engineering
Sales and finance data exploration
HR attrition model simulation
Loan eligibility and customer segmentation
Finance forecasting and telecom churn dashboards

The Automation Sandbox is a deliberate and curriculum-wide thread that grows stronger with every module you complete, ensuring your learning compounds into real workplace capability. Here's how the Automation Sandbox is integrated:

Built on a progressive learning foundation: As you advance through the 14 modules, the Automation Sandbox draws on each layer of knowledge.
Runs parallel to the core curriculum: Rather than being confined to a single session, the Automation Sandbox is woven across the program timeline.
Reinforced by industry simulations: Each Industry Simulation you complete sharpens your ability to think analytically and systematically.
Guided by structured frameworks: Supported by guided exercises and structured methodologies that help you systematically analyse your workflows.
Culminates alongside the capstone project: Just as the Capstone Project brings your technical data science skills full circle, the Automation Sandbox brings your professional process thinking full circle.

Our institute, Learners Point stand out as it brings something meaningfully different to this Data Science & ML training in KSA. We provide a regionally rooted training experience built specifically for professionals in the KSA. The reasons are as follows:

Industry-aligned and practitioner-led training
Structured batch program with peer learning
End-to-end practical learning framework
Career-focused outcomes
Trusted by professionals across the GCC

The Industry Simulation helps participants apply data science concepts by building a complete data pipeline, not isolated tasks. They collect, clean, analyse, visualise, and model business data using Python and Power BI, which mirrors how analytics work moves from raw information to usable insight.

It also connects statistics, EDA, machine learning models, and dashboarding in one practical workflow. Participants see how regression, classification, clustering, and predictive visualisation support business decisions, making the learning easier to retain and apply at work.

The Data Science & ML course in the KSA is useful for business reporting because it teaches Participants to clean, analyse, and interpret data before building reports. They work with Python, Pandas, statistics, EDA, and Power BI to move from raw datasets to structured business insight.

Participants also learn Power Query, DAX, KPI tracking, forecasting dashboards, and ML + Power BI integration. This helps them present predictive insights clearly for finance, HR, operations, customer analysis, and management reporting.

With strong Python and SQL experience, this certification in Saudi Arabia can help participants move from data handling into applied analytics and modelling. It adds statistics, hypothesis testing, EDA, feature engineering, and machine learning workflows using NumPy, Pandas, and business datasets.

Participants also gain stronger reporting value through Power BI, Power Query, DAX, forecasting dashboards, and ML + Power BI integration. This combination supports progression towards Data Analyst, BI Analyst, Machine Learning Associate, or Junior Data Scientist roles.

Yes, this training is suitable for participants who are new to programming but have some background and want to enter data science. This course starts with Python essentials, including variables, data types, loops, functions, lists, dictionaries, and basic coding workflows before moving into Jupyter/Colab, NumPy, and Pandas.

Participants then build practical confidence through data cleaning, statistics, EDA, visualisation, and machine learning models such as regression, classification, clustering, and PCA. The Industry Simulation and Power BI modules help connect learning with real business analytics work.

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