Data Science & AI Training Program
This comprehensive, hands-on training program is designed to equip learners with essential skills in Data Science and Artificial Intelligence (AI). Covering everything from foundational statistics and programming to advanced machine learning and deep learning techniques, the course blends theoretical understanding with real-world applications. Whether you're aiming for a career in data science, AI development, or intelligent business solutions, this course provides the knowledge, tools, and portfolio projects needed to succeed in today's data-driven world.
Course Objectives:
By the end of this course, participants will be able to:
  1. Understand core concepts of data science, AI, and their real-world applications.
  1. Use Python and essential libraries (NumPy, Pandas, Scikit-learn) for data analysis and modeling.
  1. Clean, visualize, and interpret complex datasets.
  1. Build and evaluate machine learning models for prediction and classification.
  1. Understand and implement deep learning using neural networks and frameworks like TensorFlow or PyTorch.
  1. Apply AI techniques in areas like natural language processing (NLP), computer vision, and recommender systems.
  1. Work on end-to-end capstone projects and prepare for entry into data-driven roles.
Target Audience:
This course is ideal for:
  • Aspiring data scientists and AI professionals.
  • IT and software developers looking to transition into AI/ML.
  • Students or recent graduates in computer science, math, statistics, or engineering.
  • Analysts and professionals seeking to upskill in data science tools and AI techniques.
  • Entrepreneurs or business leaders who want to understand and apply AI in decision-making.

by Technovate Academy

Course Content
Module 1: Introduction to Data Science & AI
  • What is data science? What is AI?
  • Data science life cycle vs. AI development pipeline
  • Real-world applications in industries
Module 2: Python for Data Science
  • Python programming essentials
  • NumPy and Pandas for data manipulation
  • Data cleaning, wrangling, and transformation
Module 3: Data Visualization
  • Exploratory Data Analysis (EDA)
  • Visualization tools: Matplotlib, Seaborn, Plotly
  • Telling stories with data
Module 4: Statistics & Probability for Data Science
  • Descriptive and inferential statistics
  • Probability distributions and hypothesis testing
  • Correlation, regression, and data patterns
Module 5: Machine Learning Foundations
  • Supervised vs. unsupervised learning
  • Algorithms: Linear/Logistic Regression, Decision Trees, KNN, Naive Bayes
  • Model training, evaluation, and cross-validation (confusion matrix, ROC, etc.)
Module 6: Advanced ML & Model Optimization
  • Ensemble methods: Random Forest, Gradient Boosting, XGBoost
  • Feature engineering and model tuning
  • Overfitting, underfitting, bias-variance tradeoff
Module 7: Deep Learning & Neural Networks
  • Introduction to deep learning
  • Architecture: neurons, layers, activation functions
  • Frameworks: TensorFlow/Keras or PyTorch
  • CNNs (for image processing) and RNNs (for sequence data)
Module 8: AI Applications
  • Natural Language Processing (NLP)
  • Text preprocessing, sentiment analysis, chatbots
  • Computer Vision
  • Image classification, object detection
  • Recommender Systems
  • Collaborative filtering and content-based systems
Module 9: AI Ethics and Deployment
  • AI fairness, transparency, and ethics
  • Model interpretability and explainability (SHAP, LIME)
  • Deploying models with Flask, Streamlit, or cloud platforms
Module 10: Capstone Project
  • End-to-end data science + AI project
  • Choose from domains like health, finance, retail, social media, etc.
  • Presentation, peer review, and instructor feedback
Course Duration
10-12
Weeks
Total program duration
2-3
Sessions/Week
Each session lasts 2 hours
40-60
Total Hours
Of comprehensive training
Bonus Features
  • 1-on-1 mentoring
  • Career guidance sessions
  • Portfolio review
Mode of Delivery
Delivery Options
Online / In-Person / Hybrid
Tools & Platforms Used
  • Python (Jupyter, VS Code)
  • TensorFlow or PyTorch
  • Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn
  • Google Colab, GitHub, Kaggle
  • Optional: AWS, GCP, or Azure intro for deployment
Materials Provided:
Downloadable notebooks and datasets
Interview prep kit and resume template for data roles
Weekly challenges and quizzes
Access to a private learner community/forum
Certification upon completion
Register Now for Limited-Time Savings
Unlock your AI career potential with exclusive early-bird pricing. Save up to 30% when you enroll this month.
Our comprehensive program delivers industry-ready skills at an exceptional value.
Limited Enrollment Period
Secure your spot before classes fill up.
Certification Included
Industry-recognized credentials at no extra cost.
Group Discounts
Additional savings for team registrations.
Click Here To Register
Technovate Academy Doha Qatar
  • Bldg 7, Street 902, Zone 52 Old Airport Road, Doha Qatar
  • +974 30914203
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