Full Stack Data Science
Learn with TheAIWhiz
9 modules
English
Lifetime access
Master the complete data science lifecycle and become a Full Stack Data Scientist.
Overview
Become a Full Stack Data Scientist and master the skills to handle end-to-end data science projects. Learn the complete data science lifecycle including problem definition, data collection, data cleaning and preprocessing, feature engineering, modeling, evaluation, and deployment. Acquire expertise in various data science tools and technologies such as Python, SQL, Tensorflow and MLOPS. This comprehensive course will equip you with the knowledge and skills to excel as a Full Stack Data Scientist.
Key Highlights
One-on-One with Industry Mentors
Designed for Working Professionals and Freshers
Dedicated Learning Management Team
Learn from Industry Practitioners
15+ Industry Projects & Case Studies
Dedicated Technical Support From Mentor
Peer Networking and Group Learning
Hackathons
What you will learn
Data science basics
Learn the fundamental concepts and principles of data science, including data preprocessing, exploratory data analysis, and data visualization.
Machine learning algorithms
Understand various machine learning algorithms such as linear regression, logistic regression, decision trees, random forests, and support vector machines.
Data manipulation and analysis
Gain hands-on experience in manipulating and analyzing data using popular Python libraries like Pandas and NumPy.
Data visualization
Learn how to effectively communicate data insights through visualizations using libraries like Matplotlib and Seaborn.
Deep learning
Explore deep learning concepts and techniques, including neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs).
Big data and cloud computing
Discover the challenges and solutions for processing and analyzing large-scale datasets using cloud computing platforms like AWS and Google Cloud.
Model deployment and production
Learn how to deploy and operationalize machine learning models to make predictions in real-world applications.
Modules
Python
12 attachments • 1 mins
Linux
3 attachments • 1 mins
1. Introduction to Linux
Linux Basics
Hands-on Sessions
SQL
2 attachments • 1 mins
SQL Basic
SQL Advance
Data Analysis, Manipulation and EDA
4 attachments
Numpy
Pandas
Matplotlib/Seaborn
Exploratory Data Analysis
Mathematics For Machine Learning
4 attachments
Linear Algebra
Calculas
Proabability
Statistics
Machine Learning
6 attachments
Supervised Machine Learning
unsupervised Machine Learning
Feature Engineering
Ensemble Machine Learning
Time Series
End to End Machine Learning Project
Deep Learning
25 attachments
Deep Learning Introduction
Perceptron
Activation Function
Forward Propagation and Backward Propagation Algorithm
Implementation - Tensorflow for Deep Learning
Gradient Descent and optimization algorithms
Regularization techniques (Dropout, L1 and L2)
Weight Initialization
Batch Normalization
Transfer Learning and pre-trained models
Convolutional Neural Network
CNN Foundation
Convolution layer, Filters, Pooling layers, Down sampling
Different types of CNN architecture
Computer vision - Object detection and localization
Computer vision - Image segmentation and instance segmentation
Computer vision - Image style transfer and generative models
Computer vision - Deep learning for video analysis and understanding
Recurrent Neural Networks (RNNs) for sequence data
RNN Foundation
LSTM and GRU
Sequence generation and language modeling
Deep Learning in NLP
Generative Models
Large Language Model
Big Data & Data Engineering
3 attachments
Introduction to Big Data And Spark
Pyspark for Data Engineering
Advanced Concepts & Spark-Hive
MLOPS and Model Deployment
2 attachments
Introduction to MLOPS
Deploy Machine Learning Model
FAQs
How can I enrol in a course?
Enrolling in a course is simple! Just browse through our website, select the course you're interested in, and click on the "Enrol Now" button. Follow the prompts to complete the enrolment process, and you'll gain immediate access to the course materials.
Can I access the course materials on any device?
Yes, our platform is designed to be accessible on various devices, including computers, laptops, tablets, and smartphones. You can access the course materials anytime, anywhere, as long as you have an internet connection.
How can I access the course materials?
Once you enrol in a course, you will gain access to a dedicated online learning platform. All course materials, including video lessons, lecture notes, and supplementary resources, can be accessed conveniently through the platform at any time.
Can I interact with the instructor during the course?
Absolutely! we are committed to providing an engaging and interactive learning experience. You will have opportunities to interact with them through our community. Take full advantage to enhance your understanding and gain insights directly from the expert.
₹ 3999.00
₹40000
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