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For Data Scientists, PhDs, Engineers, and Professionals
Move Beyond AI Theory
Master Real-World Data ScienceĀ &
Transition into High-ImpactĀ Jobs
in 8 Weeks
Learn from my 20+ Years of Hands-on Experience in AI
WatchĀ the above short video to learn how thisĀ Training can help you master Data Science
Does This Sound Like You?
ā You've taken multiple courses, yet you still donāt feel job-ready for AI roles.
ā You have some experience in AI or Data Science, but real-world applications feel overwhelming.
ā Youāre frustrated with theoretical knowledge that doesnāt translate into practical skills.
ā Despite your efforts, youāre struggling to land high-impact roles in AI.
ā You feel unsure how to move beyond just learning AI concepts to mastering them.
Youāre not aloneā¦
Ā Success Stories & Real Transformations

With my 20+ years of experience, Iāve helped over 200 professionals bridge the gap between theory and real-world AI applications.
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My hands-on training is designed to give you the practical skills and confidence to land those high-impact roles, just like my students before you.

Watch Godwin's Journey: How He Landed a Top AI Job After Completing AI Solution Mastery
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Takeaways:
- Struggling with job rejections despite having a PhD? Discover how Godwin broke into AI after facing rejection due to "lack of experience."
- Why dedication trumps certification: Godwin shares how putting in the work and asking the right questions made all the difference.
- Real-world AI vs. perfect datasets: Learn how handling real, messy data during the course helped Godwin ace his postdoc interview.
- The mentor that changes everything: Hear how the personal touch and weekly discussions propelled Godwinās confidence and success.
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THIS IS FOR YOU
If you are:
š¤Ā Professionals looking to upskill in AI and machine learning
š¤Ā Data scientists / AI Engineers wanting to specialize in end-to-end AI solutions
š¤Ā Engineers or developers who need hands-on experience with AI
š¤Ā Individuals or organizations needing practical AI implementation skills

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YOU WILL LEARN:
- Business Understanding: Analyze real-world problems for effective AI solutions.
- Data Understanding & EDA: Perform data cleaning, visualization, and exploratory analysis with Pandas, Matplotlib, Seaborn and NetworkX.
- Data Preparation: Prepare raw data for modeling, ensuring high-quality inputs.
- Feature Engineering: Implement advanced techniques to extract valuable features.
- Modeling: Build AI models including XGBoost, Deep Learning with TensorFlow/Keras, and Unsupervised Learning (Clustering, Anomaly Detection).
- Model Tuning: Optimize performance through hyperparameter tuning (Hyperopt).
- Model Evaluation: Compare models using key metrics (AUCPR) to select the best one.
- AI Fairness & Explainability: Ensure fairness with FairLearn and explain decisions with SHAP.
- Deployment: Develop web apps for model deployment (Streamlit).
YOU WILL GET:
- Unlimited Access to Pre-recorded Videos (incl. Updates)
- Private Community of Peers
- 2 x 1-hour Live Interactive Q&A with Maryam
- Weekly Hands-On Assignments
- Unlimited Access toĀ FULL Python CODE
- Completion Certificate
- Real-world Complex End to End Project (Capstone Project)
MY EXPERIENCE
Maryam'sĀ 20+ Years in AI
- PhD in AI - Machine Learning & Deep Learning
- Specialized in Computer Vision & NLP/LLMs
- Best European Researcher in Future VisionĀ
- Top Voice LinkedIn in ML and Data Science
- Chief AI Scientist of Profound Analytics
- 200+ Data Scientists are coached by me
- 20+ Years of Experience
- Best European Researcher in Future Vision
- International Projects, Awards, Publications & Books

YOUR PROGRAM
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Ā WEEK 1
Ā Ā Start the Engine (Start of 1st End to End Project)
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- šĀ Get Started
- š„Ā Introduction to AI vs Machine Learning vs Deep Learning vs DS
- š„Ā Introduction to 10 Essential Steps of Data Science (Data Science Framework to 10X Your Performance)
- š„Ā Introduction to Business Understanding - Problem Understanding & Getting the Big Picture
- š„Ā Working With Real-World Data (HANDS-ON)
- š„Ā Data Understanding - Part 1: Setup and Data in Google ColabĀ (HANDS-ON)
- š„Ā Data Understanding - Part 2: Collect and Describe DataĀ (HANDS-ON)
- š„Ā Data Understanding - Part 3: Explore and Verify Data (HANDS-ON)
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Ā WEEK 2
Ā Ā Start the Engine (Start of 1st End to End Project)
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- šĀ Assignment Week 1 - Apply Your Skills in Data Understanding & EDAĀ (HANDS-ON)
- āļøPersonal Feedback on Assignment
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Ā WEEK 3
Ā Ā AI SolutionĀ Engineered
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- š„Ā Introduction to Week 2 - Data Prep - Feature Engineering - Modelling
- š„Ā Why Data Preparation and Feature Engineering
- š„Ā Why Modelling? Which Models? Model Evaluation Method
- š„Ā ScikitLearn Library - the Golden SourceĀ Ā (HANDS-ON)
- š„Ā Data Preparation: Setup Unique IDs and Stratified Test SetĀ Ā (HANDS-ON)
- š„Ā Data Preparation: Feature TransformationĀ Ā (HANDS-ON)
- š„Ā Feature EngineeringĀ Ā (HANDS-ON)
- š„Ā ModellingĀ Ā (HANDS-ON)
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Ā WEEK 4
Ā Ā AI SolutionĀ Engineered
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- šĀ Assignment Week 2: Apply Your Skills in Data Preparation, Feature Engineering, and ModelingĀ Ā (HANDS-ON)
- āļøPersonal feedback on Assignment
- š¬Ā Q&A Live Session
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Ā WEEK 5
Ā Ā AI SolutionĀ Advance
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- š„Ā Modelling - Supervised Learning - Classification - Regression
- š„Ā Introduction to Classification Metrics
- š„Ā ML Algorithms - Naive Bayes - Logistic Regression
- š„Ā ML Algorithms - Tree - Ensemble - Gradient Descent - RandomForest - Gradient Boosting
- š„Ā Solutions to Imbalanced Data - Part I - SMOTE - ADASYN
- š„Ā Introduction to Deep Learning and Its Concepts
- š„Ā Solutions to Imbalanced Data - Part II - GANs and Oversampling with CTGANs
- š„Ā Hyperparameter Tuning
- š„Ā Hyperparameter Tuning Using Bayesian and Tree-structured Parzen Estimators
- š„Ā XGBoost Hyperparameters
- š„Ā Supervised Classification XGBoost Deep Learning Hyperparameter Tuning CTGANsĀ (HANDS-ON)
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Ā WEEK 6
Ā Ā AI SolutionĀ Advance
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- šĀ Assignment Week 3: Ensemble Classification - Deep Learning Oversampling with SMOTE, ADASYN, and CTGANs, and Hyperparameter Tuning
- āļøPersonal feedback on AssignmentĀ
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Ā WEEK 7
Ā Ā AI SolutionĀ Ultimate
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- š„Ā Introduction to ML Algorithms - Distance Similarity - KNN - Clustering - Anomaly Detection
- š„Ā Introduction to AI Explainability - Global vs Local Explainability - SHAP Values
- š„Ā Introduction to AI Fairness for Classification with Tabular Data - FairLearn Library
- š„Ā Final Model Selection - Deep Learning Ensemble Model Selection Hyperparameter TuningĀ (HANDS-ON)
- š„Ā Model Selection - Unsupervised Learning Anomaly Detection Dimensionality ReductionĀ (HANDS-ON)
- š„Ā AI Explainability - Global vs Local Explainability - SHAP ValuesĀ (HANDS-ON)
- š„Ā Hands-on AI Fairness with FairLearnĀ (HANDS-ON)
- šĀ Instruction to Install StreamlitĀ (HANDS-ON)
- š„Ā Workshop on Streamlit - Web Application Library for DeploymentĀ (HANDS-ON)
- š„Ā Complete Pipeline and Deployment with StreamlitĀ (HANDS-ON)
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Ā WEEK 8
Ā Ā AI SolutionĀ Ultimate
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- šĀ Assignment Week 4 - Unsupervised Learning, Deep Learning, Explainability, Fairness, Pipeline and DeploymentĀ (HANDS-ON)
- āļøPersonal feedback on AssignmentĀ
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š¬Ā Q&A Live Session
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Choose Your Path to AI Mastery
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AI Solutions Mastery
withĀ Mentorship
_____________________________________
āļø Community Access
āļø Personalized Feedback
āļøĀ Live Q&A / Coaching Calls
āļøĀ CompletionĀ Certificate
ā Access Course MaterialĀ
ā Real-World Project
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PRICE (excl. 21% VAT):
ā¬1995
_____________________________________
DURATION:
ā8-Weeks
šTotal 14 hours Lessons
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Ā Ā Join 200+ Trained Students NOW
ENROLL TODAYStart Learning Immediately
No Waiting Required
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ćFlexible Start Dates & Continuous Support
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I understand the importance of flexibility. Hereās how it works:
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Self-Paced Track:
- Get instant access to all lesson materials as soon as you enroll.
- Learn at your own pace and progress on your own schedule.
- Perfect for independent learners who want to dive in right away.
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Mentorship Track:
- Enjoy immediate access to lesson materials upon enrollment.
- Get twice-monthly Q&A sessions with Maryam and join an exclusive community of learners.
- Group your Q&A sessions with other students and receive personalized feedback on your real-world projects.