GtechJainx - Data Science with Python: ML and AI Training Course

Data Science with Python with ML and AI

This 270-hour course provides a deep dive into data science using Python, machine learning, and AI, focusing on practical applications, data visualization, and ethical aspects of data handling. It prepares participants for careers in data analysis and science.
270 Hrs

Key Highlights

Comprehensive curriculum

Comprehensive 270-hour course integrating Python, ML, and AI for real-world data analysis.

Practical learning

Hands-on training in Python, Excel, and advanced data science tools.

Industry expertise

In-depth exploration of machine learning and AI, including neural networks.

Career-focused training

Practical projects in data visualization using Seaborn and Matplotlib.

Data manipulate

Extensive focus on ethical considerations and effective data communication.

Flexible learning

Career-oriented outcomes with skills for data analyst and scientist roles.

What Is Data Science
Domains in Data Science
Need of Data Science
Use of Data Science in Business

Lifecycle of Data Science Projects
Data Science Tools and Technologies
Basics of Excel for Analysis
Required Skill for Data Science

Types of data
Descriptive vs Inferential Statistics
Sampling Techniques
Measures of Central Tendency and Dispersion
Hypothesis & Inferences Testing

Confidence Interval
Central Limit Theorem
P value
Variables
Co relation and Co Variance

Excel Essentials

Excel Essentials
Working with Multiple Worksheet
Cell Referencing
Working with Data Lists
Conditional Formatting

Data Validation
What-If Analysis
Formula Auditing
Protection

Formulas & Functions

Conditional Function
Text & Statistical Function
Financial Function

Creating HLOOKUP and VLOOKUP Functions
Advanced Conditional Formatting
Advanced Lookup and Reference Functions

Dashboard Designing (MIS)

Creating Dashboard
Charts & Sparkline’s
Use of Power Pivots for Data Analysis

Use of Power Queries & Power Map
Pivot table Dashboard with Slicers

Automation

Working with External Data
Exporting & Importing Data
Excel, Access, PPT, TXT, CSV

Updating Charts, Table in PowerPoint
Converting Reports into PDF
Exporting Charts, Tables to PowerPoint

Introduction to Python
Command line basics
Numbers, Operators & Comments
Variables & Strings
Boolean & Conditional Logic
Looping in Python
Lists
Dictionaries

Visualisation with Seaborn

Introduction to Seaborn
Seaborn Installation
Basics of Plotting
Plots Generation
Visualising the Distribution of a Dataset
Selection of color palettes
Lists
Dictionaries

Tuples & Sets
Functions
Modules
OOPS
File I/O
Handling Missing values(Numerical / Categorical)
Graphical Exploratory Analysis (Seaborn / Matplotlib)

Visualisation with Matplotlib

Matplotlib Installation
Matplotlib Basic Plots & it's Containers
Matplotlib components and it’s properties
Py lab & Py plot
Scatter plots
2D Plots
Histograms
Bar Graphs
Pie Charts
Box Plots

SUPERVISED LEARNING

Linear Regression / Multi-Linear Regression
Logistic Regression
Decision Tree (CART)
Ensemble Learning
Random Forest
xgBoost

K Nearest Neighbors (KNN)
Support Vector Machine (SVM)
Naive Bayes Classifier (NBC)
Grid Search CV and Random Search CV
Linear Discriminant Analysis (LDA)

UNSUPERVISED

Hierachical Clustering / Dendograms
K Means Clustering
DBSCAN

MINI BATCH K MEANS
DBSCAN
MINI BATCH K MEANS

METRICS

MAE / MSE/ RMSE / R2 and Adjusted R2
AUC ROC CURVE / Precision / Recall / F1 score / Confusion Metrics

DIMENSION REDUCTION MODELS

Kernal PCA

TIME SERIES ANALYSIS

ARIMA
FB PROPHET

HYPERPARAMETER TUNING / ADVANCED ML MODELS

Overfitting and underfitting
Cross Validation
Log Loss
Elastic net
Lasso And Ridge Regression

SMOTE
SKLEARN Using HyperParameter
Model Evalution
Gradient Descent

GIT: Complete Overview

Introduction to Git & Distributed
Version Control
Life Cycle
Create clone & commit Operations

Push & Update Operations
Stash, Move, Rename & Delete
Operations

Selecting & Retrieving Data With SQL
Filtering, Sorting, and Calculating Data with SQL
Subqueries and Joins in SQL
Modifying and Analysing Data with SQ
Architecture of Tableau
Product Components
Working with Metadata and Data Blending
Data Connectors
Data Model
File Types
Dimensions & Measures

Data Source Filters
Creation of Sets
Gantt Chart
Funnel Chart
Waterfall Chart
Working with Filters
Organising Data and Visual Analytics
Working with Mapping
Working with Calculations and Expressions
Working with Parameters
Creating Charts and Graphs
Dashboard Creation

ARTIFICAL INTELLIGENCE

overview of AI
Need of Artificial Intelligence
What is Neuron
Architecture of Artificial Neural Network
Modules
Activation Function

Optimization Function
Cost function
Dense Network
Regularization
Gradient Descent

ANN (ARTIFICIAL NEURAL NETWORK)

Simple ANN Model

CNN (IMAGE CLASSIFICATION)

Basic Intro to CNN
CNN (Convolution Neural Network)

CNN Architecture Building
Transfer Learning (VGG16 / VGG 19 / RESNET 50 / Inception V3)

NLP (NATURAL LANGUAGE PROCESSING)

Basic Intro to NLP Models
simple NLTK (stemming/ lemmatization/ regex/ stop words, corpus, unigram, bigram, trigram)
BAG of words (count vectorization)

TD-IDF-term frequency inverse document frequency
Word Embedding

GLOVE WORD 2 VEC

Fast text
Keyed vector
Text blobCertificate: G-TEC JAINx Certificate (only)

Certificate

GJX:Our Data Science with Python, ML, and AI Advanced Certificate Course sets itself apart with a comprehensive curriculum focused on data manipulation, analysis, and visualization using Python. Practical exercises and real-world projects ensure hands-on experience, guided by expert instructors with industry insight. This career-oriented program opens doors to diverse roles in data science, machine learning, and artificial intelligence, setting you up for success.
JAIN: The Certificate Course in Data Analysis stands out with its unique selling points (USPs). Through a comprehensive curriculum, you'll acquire essential skills in data manipulation, analysis, and visualization. Practical exercises and real-world examples ensure hands-on skill development. Expert instructors provide valuable guidance throughout the course, enhancing your learning experience. This career-focused training opens doors to exciting job opportunities in data analysis and equips you with the competence to handle diverse datasets effectively.

Keerti Learner Support

Throughout the course, learners will have access to dedicated support from instructors and course mentors. They can ask questions, seek clarification, and receive guidance to enhance their learning experience.
Additionally, the course provides a collaborative learning environment where students can interact with peers, share insights, and learn from each other's experiences.

GJX:Our Data Science with Python, ML, and AI Advanced Certificate Course sets itself apart with a comprehensive curriculum focused on data manipulation, analysis, and visualization using Python. Practical exercises and real-world projects ensure hands-on experience, guided by expert instructors with industry insight. This career-oriented program opens doors to diverse roles in data science, machine learning, and artificial intelligence, setting you up for success.

JAIN: The Certificate Course in Data Analysis stands out with its unique selling points (USPs). Through a comprehensive curriculum, you'll acquire essential skills in data manipulation, analysis, and visualization. Practical exercises and real-world examples ensure hands-on skill development. Expert instructors provide valuable guidance throughout the course, enhancing your learning experience. This career-focused training opens doors to exciting job opportunities in data analysis and equips you with the competence to handle diverse datasets effectively.

Data Science with Python with ML and AI

Key Highlights

Things To Know

About the Course