Certified AI & ML BlackBelt Accelerate

Working with pandas and other python libraries for data exploration

Use Matplotlib and Seaborn for data visualization

Creating charts to visualize data and generate insights

Univariate and Bivariate analysis using python

Perform Statistical Analysis on real-world datasets

Build and Validate Hypothesis using statistical tests

Generating useful insights from the data

Importing and working with different kinds of data in Tableau

Build bubble charts, geo-location charts, and many others

Learn to create Dashboards in Tableau

Master storyboarding in Tableau

Learn to create engaging presentations

Perform feature engineering in Tableau

Become familiar with data manipulation in Tableau

Dealing with ambiguous business problems

Structure a business problem into a data science problem

Understanding the Machine Learning Lifecycle

Key Frameworks for each stage in ML Lifecycle

Present analysis and business insights in an impactful manner

Communicate ideas and insights to the stakeholders

Learn Important Machine Learning concepts

Perform data cleaning and Preprocessing

In-depth understanding of Basic ML models

Linear Models, Decision Tree, k-NN

Math Behind each Machine Learning Algorithm

Building Classification and Regression Models

Hyperparameter Tuning to improve model

Solving real-world business problems using Machine Learning

Learn the art of Feature engineering

Feature Generation from time-series data

Automated Feature Engineering Tool

Concept of dimensionality reduction

Feature Selection and Elimination Techniques

Detailed Understanding of Principal Component Analysis (PCA)

Concept of Factor Analysis

Explore the Advanced ML concepts and Algorithms

Use Ensemble Learning Techniques (Stacking and Blending)

Understand and Implement Bagging and Boosting Algorithms

Learn to handle Text data and Image Data

Working with structured and unstructured data

Dealing with unsupervised learning problems

Clustering Algorithms including k-means and Hierarchical clustering

Important concepts of Deep Learning

Working of Neural Network from Scratch

Activation Functions and Optimizers for Deep Learning

Understand Deep Learning architectures (MLP, CNN, RNN and more)

Explore Deep Learning Frameworks like Keras and PyTorch

Learn to tune the hyperparameters of Neural Networks

Build Deep Learning models to tackle real-life problems

Recommender Systems in industry

Detailed Taxonomy of types of Recommender Systems

Collaborative Filtering Methods

Content-Based Recommender Systems

Knowledge-Based & Hybrid Recommender Systems

Market Basket Analysis & Association Rules

Evaluation of Recommender Systems

Build Book recommender System and other real-life projects

Important concepts of Time Series Forecasting

Machine Learning techniques for Time Series forecasting

Validation techniques for Time series data

Framework to evaluate Time Series Models

Exponential Smoothing Methods for forecasting

Reading ACF and PACF plots

Tuning Parameters for ARIMA

ARIMA and SARIMA Model

Deep Learning for time series

Solve Real-world business problems

Understanding the different roles in Data Science

Dos and Don'ts for Resume Building

Tips and strategies to build the perfect resume

Preparing for Data Science Interviews

Understanding the important skills required

How to build your digital Presence

Tips and Tricks to Ace Data Science Resume

List of Interview Questions for Data Science