Datrist Full Stack Data Scientist BootCamp

Course Curriculum

Course Curriculum walkthrough

Introduction

Sample Projects In The Course
The Big Picture
Data Science Overview
What is Data Science
DA vs DS vs AI vs ML
Industries That Use and Hire Data Scientist
Applications of Data Science
Data Science Lifecycle and the Maturity Framework
Who is a Data Scientist
Career Opportunities In Data Science
Typical Backgrounds of Data Scientists
The Ultimate Path To become a Data Scientist(Skills you need to develop)
Typical Salary of a Data Scientist

SQL BEGINNER LEVEL

SQL COMMANDS

UNDERSTANDING AND CREATING SQL DATABASES

UNDERSTANDING AND CREATING SQL TABLES

TYPES OF SQL KEYS

DATA TYPES IN SQL

CREATE TABLE AND INSERT DATA INTO TABLE

SQL CONSTRAINTS

WEEK 2 SQL INTERMEDIATE LEVEL

SQL JOINS

WORKING WITH EXISTING SQL TABLE

SQL VIEW

SQL DATA SUMMARIZATION AGGREGATION FUNCTIONS

ADVANCE SQL FUNCTIONS

SQL STORED PROCEDURE

TRIGGERS

TRANSACTION

FULL PYTHON FOR DATA SCIENCE COURSE

HANDS-ON WITH PYTHON

PYTHON OUTPUT(), INPUT() AND IMPORT() FUNCTIONS

PYTHON OPERATORS

PYTHON FLOW CONTROL

WEEK 2 PYTHON FUNCTIONS

PYTHON GLOBAL AND LOCAL VARIABLES

WORKING WITH FILES IN PYTHON

PYTHON MODULES

PYTHON PACKAGES AND LIBRARIES

DATA TYPES IN PYTHON

EXTRA CONTENT

WEEK 3 NUMPY

Introduction To Numpy
Numpy Creating Multi-Dimensional Arrays
Numpy Arange Function
Numpy Zeros, Ones and Eye functions
Numpy Reshape Function
Numpy Linspace
Numpy Resize Function
NumpyGenerating Random Values With random.rand
NumpyGenerating Random Values With random.randn
Numpy Generating Random Values With random.randint
Numpy Indexing & Slicing
Numpy Broadcasting
Numpy How To Create A Copy Dataset
Numpy- DataFrame Introduction

WEEK 4 PANDAS

Pandas- Series 1
Pandas- Series 2
Pandas- Loc & iLoc
Pandas- DataFrame Introduction
Pandas- Operations On Pandas DataFrame
Pandas- Selection And Indexing On Pandas DataFrame
Pandas- Reading A Dataset Into Pandas DataFrame
Pandas- Adding A Column To Pandas DataFrame
Pandas- How To Drop Columns And Rows In Pandas DataFrame
Pandas- How To Reset Index In Pandas Dataframe
Pandas- How To Rename A Column In Pandas Dataframe
Pandas- Tail(), Column and Index
Pandas- How To Check For Missing Values or Null Values(isnull() Vs Isna())
Pandas- Pandas Describe Function
Pandas- Conditional Selection With Pandas
Pandas- How To Deal With Null Values
Pandas- How To Sort Values In Pandas
Pandas- Pandas Groupby
Pandas- Count() & Value_Count()
Pandas- Concatenate Function
Pandas- Join & Merge(Creating Dataset)
Pandas-Join
Pandas- Merge

DATA VISUALISATION MATPLOTIIB AND SEABORN

PYTHON PROJECTS

2ND MONTH FULL STATISTICS FOR DATA SCIENCE

STATISTICAL METHODS DEEP DIVE

DATA

FREQUENCY DISTRIBUTION

CENTRAL TENDENCY

MEASURES OF DISPERSION

THE FIVE NUMBER SUMMARY & THE QUARTILES

THE NORMAL DISTRIBUTION

CORRELATION

3RD MONTH WEEK 1 PROBABILITY

HYPOTHESIS TESTING

Introduction To Hypothesis
Null Vs Alternative Hypothesis
Setting Up Null and Alternative Hypothesis
One-tailed Vs Two-tailed test
Key Points On Hypothesis Testing
Type 1 vs Type 2 Errors
Process Of Hypothesis testing
P-Value
Alpha-Value or Alpha Level
Confidence Level

GITHUB FOR DATA SCIENCE

WEEK 2 FULL MACHINE LEARNING COURSE

USE CASE

MACHINE LEARNING ALGORITHMS

WORKING WITH MACHINE LEARNING DATA

Considerations When Loading Data
Loading Data from a CSV File
Loading Data from a URL
Loading Data from a Text File
Loading Data from an Excel File
Skipping Rows while Loading Data
Peek at your Data
Dimension of your Data
Checking Data Types of your Dataset
Descriptive Statistics of your Dataset
Class Distribution of your Dataset
Correlation of your Dataset
Skewness of your Dataset
Missing Values in your Dataset
Histogram of Dataset
Density Plot of Dataset
Box and Whisker Plot
Correlation Matrix
Scatter Matrix(Pairplot)

WEEK 3 SUPERVISED MACHINE LEARNING ALGORITHMS

What is Regression
Introduction to Linear Regression
Planes and Hyperplane
MSE vs RMSE
LAB SESSION Training Data vs Validation Data vs Testing Data
LAB SESSION Splitting Dataset into Training and Testing
Linear Regression LAB 1
Linear Regression LAB 2(PART 1)
Linear Regression LAB 2(PART 2)

LOGISTIC REGRESSION ALGORITHM

NAIVE BAYES ALGORITHM

K-NEAREST NEIGBHOR ALGORITHM (KNN)

SUPPORT VECTOR MACHINE (SVM) ALGORITHM

MACHINE LEARNING ALGORITHM PERFORMANCE METRICS

Overview
Confusion Matrix True Positive False Positive True Negative False Neg.
Accuracy
Overview Of Existing Databases
Precision
Recall
The Tug of War between Precision and Recall
The SELECT Statement in Details
F 1 Score
Classification Report
The ORDER BY Clause
LAB SESSION AUC and ROC

DECISION TREE ALGORITHM

Decision Tree Overview
The WHERE Clause
CART Introduction To Decision Tree
Purity Metrics Gini Impurity Gini Index
Calculating Gini Impurity (PART 1)
Operation with SELECT statement
Calculating Gini Impurity (PART 2)
Information Gain
Overfitting in Decision Trees
Aliasing in SQL
Prunning

WEEK 4 ENSEMBLE TECHNIQUES

Exercise 1 and solution
Introduction To Ensemble Techniques
Difference bn Random Forest & Decision Tree
The DISTINCT Keyword
Why Random Forest Algorithm
More on Random Forest Algorithm
Introduction to Bootstrap Sampling Bagging
WHERE Clause with SQL Comparison operators
Understanding Bootstrap Sampling
Diving Deeper into Bootstrap Sampling
Bootstrap Sampling summary
Exercise 2 and Solution
Bagging
Boosting
Adaboost Introduction
The AND, OR and NOT Operators
The Maths behind Adaboost algorithm
Gradient Boost Introduction
Gradient Boosting An Intuitive Understanding
Exercise 3 and Solution
The Mathematics behind Gradient Boosting Algorithm
XGBoost Introduction
Maths of XGBoost (PART 1)
The IN Operator
Maths of XGBoost (PART 2)
LAB SESSION 1 Ensemble Techniques
LAB SESSION 2 Ensemble Techniques
Exercise 4 and Solution
Stacking An Introduction
LAB SESSION Stacking

OVERFITTING AND UNDERFITTING

BIAS VS VARIANCE

UNSUPERVISED MACHINE LEARNING ALGORITHMS

WEEK 3 K-MEANS CLUSTERING ALGORITHM

HIERARCHICAL CLUSTERING ALGORITHM

PRINCIPAL COMPONENT ANALYSIS (PCA)

FEATURE ENGINEERING MODEL SELECTION & OPTIMIZATION

KFold Cross Validation
LAB SESSION KFold Cross Validation
Bootstrap Sampling
Leave One Out Cross Validation(LOOCV)
LAB SECTION LOOCV
Hyper-parameter Tuning An Introduction
Hyper-parameter Tuning Continue
RandomSearchCV An Introduction
LAB SESSION 1 GridSearchCV
LAB SESSION 2 GridSearchCV
LAB SESSION RandomSearchCV

WEEK 3 WEB SCRAPING

PROJECT WIKIPEDIA WEB SCRAPING

PROJECT ONLINE BOOK STORE WEB SCRAPPING

PROJECT (WEB SCRAPING) BUILDING AMAZON AUTO SCRAPER

RECOMMENDATION SYSTEMS

Recommendation System An Overview
Where Recommender Systems came from
Applications of Recommendation Systems
Why Recommender Systems
Types of Recommender Systems
Popularity based Recommender Systems
Content-based Filtering An Overview
Cosine Similarity
Cosine Similarity with Python
Document Term Frequency Matrix
LAB SESSION Building Content-based Recommender Engine
Collaborative Filtering An Introduction
Evaluation Metrics for Recommender Systems

BANK NOTE ANALYSIS

BIG MART SALES PREDICTION

AMAZON.COM EMPLOYEE ACCESS CHALLENGE

BREAST CANCER DETECTION USING SVM AND KNN PART 1

PREDICTING COMPRESSIVE STRENGTH OF CONCRETE

STOCK MARKET CLUSTERING

STREAMLIT FOR BUILDING MACHINE LEARNING APPS

FLASK TUTORIAL

WEEK 1 END-TO-END MACHINE LEARNING WITH DEPLOYMENT PREDICT RESTAURANT RATING

CLOUD HEROKU MACHINE LEARNING CLOUD DEPLOYMENT

CLOUD AMAZON WEB SERVICE (AWS) DEPLOYMENT

CLOUD MICROSOFT AZURE DEPLOYMENT

ML PROJECTS BUILDING A NETFLIX RECOMMENDATION SYSTEM

Building a Netflix Recommendation System
Data Preparation (PART 1)
Data Preparation (PART 2)
Data Preparation (PART 3&4)
Data Preparation (PART 3&4) Con’t
Data Preparation (PART 5)
Main.py (PART 1.1)
Main.py (PART 1.2)
Main.py (PART 2)
Preparing HTML Files 1.1
Preparing HTML Files 1.2
Preparing HTML Files 2.1
Preparing HTML Files 2.2
Final Heroku Cloud Deployment
Optional How to Fix Errors when deploying

ML PROJECTS BUILDING CRUD APP

ML PROJECT BUILDING COVID-19 REPORT DASHBOARD FOR BERLIN CITY

ML PROJECTS BUILDING IPL SCORE PREDICTOR APP

ML PROJECTS BUILDING A SALES FORCAST APP

ML PROJECTS BUILDING A BREAST CANCER PREDICTOR APP PART 2

WEEK 4 SCIENTIFIC RESEARCH PAPER

ARTIFICIAL INTELLIGENCE

WEEK 1 DEEP LEARNING

WEEK 2 ACTIVATION FUNCTIONS

TENSORFLOW AND KERAS

LAB SESSION DEEP LEARNING(ANN)

LAB SESSION 1 Building your first Neural Network
LAB SESSION 2 Building your first Neural Network
Handling Overfitting in Neural Network
L2 Regularisation
Dropout for Overfitting in Neural Network
Early Stopping for overfitting in NN
ModelCheck pointing
Load best weight
Tensorflow Playground
1 Building Your Third Neural Network with MNIST
2 Building Your Third Neural Network with MNIST

COMPUTER VISION (CV) BEGINNER LEVEL

CPU VS GPU VS TPU

COMPUTER VISION INTERMEDIATE LEVEL

Understanding Convolution (PART 1)
Understanding Convolution (PART 2)
Convolution Operation
Understanding FilterKernel Feature Map Input Volume Receptive Field
Stride and Step Size
Padding
Pooling
Understanding CNN Architecture
LAB SESSION CNN Lab 1
LAB SESSION CNN Lab 2

CNN ARCHITECTURES

TRANSFER LEARNING

OBJECT DETECTION

PERFORMANCE METRICS FOR OBJECT DETECTION

OBJECTION DETECTION TECHNIQUES

Overview
Brute Force Approach
Sliding Window
Region Proposal
R-CNN
Fast R-CNN
ROI Pooling
Faster R-CNN
State-of-the-Art Algorithms
YOLO
LAB SESSION 1 YOLO LAB Overview
LAB SESSION 2 YOLO
LAB SESSION 3.1 YOLO
LAB SESSION 3.2 YOLO
SSD

WEEK 1 OPENCV FULL TUTORIAL

Introduction To OpenCV
Opencv Installation
Opencv Setup
Reading Images
Reading Video
Stacking Images together
OpenCV Join
IMAGE Face Detection with OpenCV
VIDEO Face Detection with OpenCV
Live Streaming with OpenCV
OpenCV Functions
Image Detection Techniques
Edge Detection
Dilation and Erode
OpenCV Conventions
Adding Shapes
Creating Lines
Creating Shapes(Rectangle)
Warp Perspective
Adding Text

CV PROJECT CAR PARKING SPACE COUNTER USING OPENCV

CV PROJECT(KAGGLE) FRUIT AND VEGETABLE CLASSIFICATION

CV PROJECT PREDICTING LUNG DISEASE WITH COMPUTER VISION

WEEK 2 CV PROJECT NOSE MASK DETECTION WITH COMPUTER VISION

CV PROJECT POSE DETECTION

CV PROJECT BUILDING A VIRTUAL AI KEYBOARD

CV Project Building AI Virtual Keyboard
Building AI Virtual Keyboard (PART 1)
Building AI Virtual Keyboard (PART 2)
Building AI Virtual Keyboard (PART 3)
Building AI Virtual Keyboard (PART 4)
Building AI Virtual Keyboard (PART 5)
Building AI Virtual Keyboard (PART 6)
Building AI Virtual Keyboard (PART 7)
Building AI Virtual Keyboard (PART 8)

CV PROJECT Yolov4 Object Detection Using Webcam

WEEK 3 NATURAL LANGUAGE PROCESSING(NLP)

Overview
Recapitulation
What is NLP
Applications of NLP
The Must-Know NLP Terminologies
Word
Tokens and Tokenizations
Corpus
Sentence and Document
Vocabulary
Stopwords

HANDS-ON NLP TEXT PRE-PROCESSING

TEXT PRE-PROCESSING NORMALIZATION

WEEK 4 PART OF SPEECH (POS) TAGGING

HANDS-ON TEXT PRE-PROCESSING

INTRODUCTION TO STATISTICAL NLP TECHNIQUES

WEEK 1 INTERMEDIATE LEVEL WORD EMBEDDINGS

WORD2VEC

GLOVE

SENTENCE PARSING

SEQUENTIAL MODELS

WEEK 2 ADVANCED LEVEL RECURRENT NEURAL NETWORK (RNN)

What is a Recurrent Neural Network (RNN)
Types of RNNs
Use Cases of RNNs
Vanilla Neural Network (NN) vs Recurrent Neural Network (RNN)
Backpropagation Through Time (BTT)
Mathematics Behind BTT
Vanishing and Exploding Gradient
The problem of Long Term Dependencies
Bidirectional RNN (BRNN)
Gated Recurrent Unit(GRU)

LSTM

SEQUENCE TO SEQUENCE MODELS (SEQ2SEQ)

WEEK 3 NLP PROJECT SENTIMENT ANALYZER

NAME ENTITY RECOGNITION (NER)

NLP PROJECT BUILDING A NAME ENTITY RECOGNITION APP

NLP PROJECT AI RESUME ANALYZER APP

WEEK 4 MICROSOFT POWER BI

Power BI An Introduction
Installation
Query Editor Overview
Connectors and Get Data Into Power BI
Clean up Messy Data (PART 1)
Clean up Messy Data (PART 2)
Clean up Messy Data (PART 3)
Creating Relationships
Explore Data Using Visuals
Analyzing Multiple Data Tables Together
Writing DAX Measure (Implicit vs. Explicit Measures)
Calculated Column
Measure vs. Calculated Column
Hybrid Measures
The 8020 Rule
Text, Image, Cards, Shape
Conditional Formatting
Line Chart, Bar Chart
Top 10 ProductsCustomers

9TH MONTH Hackathons and Finding Internships & Jobs

Course Content

Course Curriculum

Course Curriculum walkthrough

Introduction

Sample Projects In The Course

The Big Picture

Data Science Overview

What is Data Science

DA vs DS vs AI vs ML

Industries That Use and Hire Data Scientist

Applications of Data Science

Data Science Lifecycle and the Maturity Framework

Who is a Data Scientist

Career Opportunities In Data Science

Typical Backgrounds of Data Scientists

The Ultimate Path To become a Data Scientist(Skills you need to develop)

Typical Salary of a Data Scientist

SQL BEGINNER LEVEL

Introduction To SQL for Data Science

Types of Databases

What is a Query

What is SQL

SQL Installation

SQL Installation Guide For MacOS

SQL Installation Guide For Windows

Extra Help in Installing SQL

Overview of SQL workbench

SQL COMMANDS

Introduction To SQL Commands

SQL CRUD Commands

UNDERSTANDING AND CREATING SQL DATABASES

SQL Schema

Inserting Comments in SQL

Creating Databases

UNDERSTANDING AND CREATING SQL TABLES

Overview of SQL Table

TYPES OF SQL KEYS

Keys in SQL

Primary Key

Foreign Key

Composite Key

Super Key

Alternate Key

DATA TYPES IN SQL

SQL Data Types

CREATE TABLE AND INSERT DATA INTO TABLE

CREATE Table

INSERT Data

SQL CONSTRAINTS

Understanding SQL Constraints

NOT NULL & UNIQUE Constraints

DEFAULT Constraints

PRIMAY KEY Constraint

Alter SQL Constraint

Adding and Dropping SQL Constraint

Foreign Key Constraint

WEEK 2 SQL INTERMEDIATE LEVEL

Creating Exiting Databases

SQL JOINS

Introduction To SQL JOINS

Exercise 10 and Solution

Joining Across Multiple Databases

Exercise 11 and Solution

Joining Table to Itself

Joining Across Multiple SQL Tables

LEFT and RIGHT JOIN

Exercise 12 and Solution

Exercise 13 and Solution

WORKING WITH EXISTING SQL TABLE

INSERTING Multiple Data Into Existing Table

Creating A Copy of a Table

Updating Existing Table

Updating Multiple Records In Existing Table

SQL VIEW

Create SQL VIEW

Using SQL VIEW

Alter SQL VIEW

Drop SQL View

SQL DATA SUMMARIZATION AGGREGATION FUNCTIONS

COUNT () Function