Address
3rd Floor, 301-Bhawarkua Square, Indrapuri Main Rd, Above Canara Bank, Near Scholar's Career Academy, Indore, Madhya Pradesh 452001
Call Us
+91 9399200960
RoadMap to be a Data Scientist
Masters Program in Artificial Intelligence & Machine Learning
(Duration - 6 to 6.5 Months)
LEVEL-1
Python Programming(Basic to Advanced Level)
- Introduction to Python Basic
- Introduction to Python Object
- Python Data Types
- Conditional Statements
- Iterators
- Loops and its implementations
- Functional Programming
- Modular Programming
- Data Scientists tool pack
- Data Visualization using Matplotlib &Seaborn
- Python Code Debugging and Troubleshooting Techniques
- Python Code Optimization Techniques
- Hacking Techniques using Python
- Data Analytics Project using Python
- OOPS concepts
- SOLID Principals
- Modules & Packages
LEVEL-2
Business Decision Making using Statistics
- Introduction
- Random Variables
- Descriptive Statistics
- Inferential Statistics
- Probability Concepts
- Probability Distributions
- Binomial, Poisson and Normal Distributions
- Probability for Business Decision Making
- Exploratory Data Analysis
- Presentation of Data
- Hypothesis Formation
- Hypothesis Testing
- Z-test
- T-test
- Chi Square test
- Implementation of hypothesis in business use cases
- Analysis of Variances (ANOVA)
LEVEL-3
Supervised Machine Learning Algorithms
- Linear Regression
- Group Project and Presentation
- Logistic Regression
- Naïve Bayes
- Support Vector Machines
- K- nearest neighbors (KNN)
- Model Selection Rationale
- Model Hyper Parameter Tuning
- Classification and Regression Tree (CART)
- Random Forest
- Boosting Techniques
- Bagging Techniques
- K- fold Cross Validation
LEVEL-4
Unsupervised Machine Learning
- Different Distance Measures
- Hierarchical Clustering
- K- means Clustering
- K- medoid Clustering
- Partition Around Medoids Clustering
- Feature Selection Techniques
- Principal Component Analysis
LEVEL-5
MySQL & MongoDB in Practice
- Introduction of MySQL
- Installation of MySQL
- Installation of SQL Workbench
- CRUD Operations in SQL
- Introduction to Mongo DB
- Integration of Python with MySQL
- What is Mongo DB?
- SQL vs No SQL DB
- ACID Property
- Cap Theorem
- Where to implement NoSQL DB
- Understanding of basics like Collection, Document etc.
- Introduction to JSON
LEVEL-6
Data Visualization
- Power BI
- Tableau
- Seaborn
- Matplotlib
- Plotly
- Exploratory Data Analysis (EDA)
- Project on EDA
LEVEL-7
Deep Learning & Natural Language Processing (NLP)
- Artificial Neural Networks
- Backward & F/W propogation
- Tensorflow
- Keras
- Development of a Deep Learning Model
- What is NLP?
- Text Processing
- Noise Removal
- Lexicon Normalization
- Object Standardization
- Features Identification on Text
- Syntactical Parsing
- Entity Parsing
- Statistical Features
- Word Embedding
- Important NLP Tasks
- Classification
- Text Matching
- Conference Resolution
- Regular Expressions
LEVEL-8
Model Hyperparameter Tuning & Project Deployment Toolbox
- Building Efficient Machine Learning Project Pipelines
- Machine Learning model hyper-parameter tuning
- Development of a scalable ML model
- Designing Web Interface using Python Flask
- Use of Git and GitHub
- Use of Docker in industry grade models
- Introduction to AWS
- Deployment of Machine Learning Models on AWS
- Model Maintenances on Cloud in Practice
LEVEL-9
Industry Preparations
- Resume Scaling
- LinkedIn Profile Optimization
- Working on GitHub and Open-Source Contribution
- Data Structures and Algorithms based questions
- Mock Interview Session’s
- Agile Methodology