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Begin your learning experience and become an ai data analyst with certificate courses curated to land your dream job.
Skills Covered in this Path
- Data Analytics
- Problem-solving
- Insights
- Predictive Modeling
- Business Intelligence
- Data Science Process
- Data Preprocessing Techniques
- Data Science Components
- Career Trajectory
- Programming Basics
- Data Handling using Python
- Numpy and Pandas
- Python Basics
- NumPy
- Pandas
- Matplotlib
- Seaborn
- Plotly
- Basics of Probability
- Marginal Probability
- Bayes Theorem
- Probability
- Population
- Samples
- Statistical analysis
- Hypothesis testing
- Statistical distributions
- Business Intelligence Fundamentals
- Data Visualization Principles
- Introduction to Tableau
- Understanding Data Types
- Navigating the Tableau Interface
- Creating Dashboards
- Visual Analytics Techniques
- Hands-on Tableau Exercises
- Integrating Data Sources.
- Power BI usage
- data loading
- creating reports
- dashboards
- slicers & filters
- visual interactivity
- Practical visualization walkthrough
- IPL data analysis with Python
- Data Description
- Basic Data Understanding
- Data Manipulation
- Skewness Using Histograms & Density Curves
- Visualising Outliers Using Boxplots
- Visualising Correlation Using Scatter Plots/Heatmaps
- What Is Machine Learning
- Regression Analysis
- Linear Reg
- Python
- Statistics
- Reinforcement learning
- Machine learning
- ANN
- Tensorflow
- Keras
- Gradient
- Backpropagation
- Reinforcement Learning
- States
- Actions
- State based mechanism in Reinforcement Learning
- AI Fundamentals
- Python for AI
- Neural Networks Basics
- Biological vs. Artificial Neurons
- Perceptron Mechanism
- ANN Architecture
- Activation Functions
- Forward Propagation
- Loss Functions
- Keras Framework
- Gradient Descent
- MNIST Application
- TensorFlow
- Data augmentation
- Model training & tuning
- Regularization
- Image processing (NNs)
- Feature & object detection
- Image classification
- CV problem-solving
- Pixel & image manipulation
- Image processing
- OpenCV with Python
- TensorFlow
- MNIST Dataset
- Covid-19 detection
- Tokenization
- stemming
- lemmatization
- removing stopwords
- NLP modeling techniques
- machine learning
- logistic regression
- sentiment analysis
- TextBlob
- TextBlob sentiment analysis
- U-Net
- semantic segmentation
- NLP Use-cases
- NLP Project
- Forecasting using Python
- Exponential Smoothing
- ARIMA
- Time Series in R
- Feature Selection
- Linear Discriminant Analysis with Python
- Flask
- Model Deployment
- Model Deployment
- Heroku
- DevOps Fundamentals
- Version Control With Git
- Containerization Using Docker
- Continuous Integration
- Jenkins Setup
- DevOps Lifecycle
- Automation Practices
- Software Deployment
- Monitoring Tools
- Collaboration In DevOps Teams
- Docker
- Docker Best practices
- Optimizing Docker Files
- Docker
- Docker Storage
- Docker Network
- Docker Compose
- Docker
- grafana
- prometheus
- Docker Monitoring
- Docker
- Docker swarm
- Orchestration
- AWS ECR
- AWS ECS
- Docker
- grafana
- prometheus
- Docker Monitoring
- Spring boot
- Deployment
- Version Control
- Git
- GitHub
- Git Vs GitHub
- Accessing GitHub
- Touring GitHub
- Creating Repository
- Committing Changes
- Branching
- Merging
- Pull Requests
- Basic Git Workflow
- Creating Git Profile
- R programming fundamentals
- variables
- data types
- data structures
- control structures
- functions
- packages
- importing data into R
- manipulating data in R
- performing statistical analysis in R
- data cleaning and wrangling
- statistical modeling
- Time series analysis
- Model forecast theory
- Time Series Forecasting
- Time Series Demo
- OpenCV
- Face Detection
- Face Recognition
- Deep Learning
- OpenCV Operations
- Face Detection demo
- Face Detection
- Face Recognition
- Applications of Face Recognition
- Face Detection using OpenCV using Python
- Healthcare analytics
