منهج تدريبي
محتويات الكورس
01
Download required tools
02
Data Types
03
Configuring Anaconda
04
Strings
05
Python basic Syntax
06
Containers
07
Conditions
08
Loops
09
Strings
10
Functions
11
Files Databases
12
Reusability
01
Introduction to OOP and how to use them in AI
02
Handling Projects in Business
03
Complexity Analysis
✨Project: Python problems - Build OOP Projects
01
Importance of Data Structures
02
Data Structures in AI
03
Data Structures usecases
04
Graphs
01
Introduction to Data Science
02
Data Pipeline
03
History of Data
04
Importance of data in business
05
Introduction to Data Science, Data Analysis and Data Engineering
06
DataOps Pipeline
07
History of Data
08
Importance of data in business
09
Data Tools
01
Data pipeline
02
Importance of statistics in Al
03
Important statistics rules in Al (mean, median, mode, variance, sti... etc.)
04
Sampling techniques
05
Statistical test
06
Hypothesis testing
01
How to use linear algebra in Data Analysis
02
Basic Algebra rules
03
Matrix multiplication
01
Why do we use probability?
02
Conditional probability
03
Unconditional Probability
04
Probability distribution
✨Project: Analyzing Real Data with Statistics for AI.
01
Calculus in Al
02
Differentiation
03
Weights optimization
04
Partial Clerative
05
Chain Rule
01
History of Data
02
Importance of data in business
03
Important tools to use in data science
01
Web scrapping (beautiful soup, requests)
02
feature extraction
03
data filtering and data manipulation
04
Scrapping tools
05
Automatic scrapping
01
Dealing with dataset
02
Extracting information from dataset
03
Data Handing and formatting
04
Creating Dataframes
05
Automatic Data Cleaning
06
Automatic Data Analysis
01
Matplotlib basics (charts, modeling, matplotlib with dataframes)
02
Seabom basics
03
Automatic Visualization
04
Sweetvir
01
How to transform data into vectors?
02
Work with real datasets
03
getting started with Kaggle
01
openCV basics
02
face detection, recognition
03
object detection
04
Medlapipe
✨Project: End-to-End Data Projects - Report Generation
01
Wave analysis >
02
Sampling
03
Quantization
04
Audio Visualization
✨Project: End-to-End Data Projects - Report Generation - Story Telling
01
Cloud-Based Platforms (Google Colab -Amazon SageMaker -IBM Watson - MS Azure ML)
02
SQL
03
Recommendation systems
04
Financial Analysis
05
PoweBI
06
Tableau
07
How to write your data schema
08
How to report your insights
09
Story telling
10
How to work with any data base in python and PowerBI
01
History of Machine Learning
02
Types of Machine Learning
03
Types of Problems AI can solve
01
What is Classification
02
Logistic Regression
03
Support vector machine
04
K Nearest Neighbors
05
Decision Tree
06
Random forest
07
Xgboost regression
08
Decision Tree Regression
09
LASS Oregression
10
SVM Regression
11
Neural Network regression
01
Begging
02
Decision Tree Regression
03
LASSO Regression
04
Random Forest Regression
05
Ridge Regression
06
SVM Regression
07
Boosting
08
Stacking
09
Xgboost regression
10
Neural Network regression
01
Calculus in AI
02
Clustering in business
03
K-Means Clustering
04
Mean Shift Clustering
✨Project: Implementation from Scratch for important models -
Tips & tricks for Interviews - MOC Interview
01
Saving Your model
02
Uploading your model
03
Create an APt
04
Connecting to your model
01
What is deep learning
02
Why and when to use it
03
Deep learning and Neuroscience
04
TensorFlow VS Pytorch Vs Onnx
01
Auto ML
02
Tpot
03
Clear ML
04
N2O
05
ML flow
01
ANN Intuition
02
Forward & Backward propagation
03
Error functions and optimization
04
Activation functions
05
Implementation from Scratch
01
Neural networks for Image classification
02
Pretrained models & Transfer Learning
03
Inception model
01
Time Series Analysis
02
Network Feedback
01
Network memory
02
Implementation approaches
01
Generative Architectures
02
Deep fake networks
03
IBM Watson
04
Applying Al in real life applications
05
Chatbots basics
06
Chatbots basics
07
wit.ai
01
Advanced neural networks
02
Applying computer vision in medical fields
03
Applying computer vision in medical fields
04
Medical data types (CT scans, dicom files, etc..)
05
Working with 3D data types
06
image segmentation
07
3D CNN
08
Object Detection
09
No code models
10
Data Augmentation
11
Data Annotation
12
Data Annotation
01
Intro to Hugging Face
02
Hugging Face API
03
Deploying Hugging Face models
✨Project: Building a Simple Image Classification Model.
01
Al Automation
02
Cronjobs
03
Intro to Reinforcement learning
04
References
05
Questions and answers
06
Project selection
01
Currency Classifier
02
Face rocognition/ detection Course Projects
03
Text classification
04
Market predection
05
Music Recommendation system
06
Movie Recommendation ststem
07
Cancer detection
08
Multi user Chatbot
09
image generator using GANs
10
Scrapping data from instegram We will be working with over 30 datasets from different types (Le images, string, numbers etc...)
01
أكثر من 10 مشاريع.
02
استخلاص رؤى من جميع أنواع البيانات.
Conclude Insights from all kinds of Data
03
إجراء جميع عمليات المعالجة المسبقة للبيانات اللازمة لأي مشكلة.
Perform all Data preprocessing required for a problem.
04
إنشاء مجموعات بيانات بناءً على المشكلة. وقواعد البيانات.
Generate Datasets based on the problem
05
اختيار المنهجية الأنسب لحل أي مشكلة تحسين.
Choose the best methodology to solve any optimization problem
06
إتقان الأدوات الرئيسية لعلم البيانات.
Mastering main tools of Data Science
07
ضبط النماذج وتخصيص هياكلها. Fine tune models and customize architectures
08
مقابلات تجريبية + تدريب مهني (Mock Interviews + Career Coaching)
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