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Data Science with Machine Learning & AI

Our Data Science with AI course teaches you to harness the power of machine learning, deep learning, and AI to solve real-world problems. Learn how to analyze data, build predictive models, and apply AI techniques in various industries. Gain hands-on experience with Python, TensorFlow, and other tools.

Description

The Data Science with AI course equips you with essential skills in data analysis, machine learning, and artificial intelligence. You will master data manipulation, statistical analysis, and algorithm development using Python and popular libraries like NumPy, Pandas, and Scikit-learn. Dive into machine learning models, neural networks, and deep learning frameworks like TensorFlow and Keras. Learn to analyze complex datasets and build predictive models that offer insights for business decisions. Understand key AI concepts such as natural language processing and computer vision. This course prepares you for careers in data science, AI, and analytics, with a focus on practical applications and hands-on projects. By the end, you will be capable of applying AI techniques to real-world challenges and opportunities.

What You will Learn?

  • Understand the basics of Python programming and its application in data science and AI.
  • Learn how to manipulate, analyze, and process large datasets using libraries like Pandas and NumPy.
  • Master machine learning techniques and algorithms such as regression, classification, and clustering.
  • Gain hands-on experience with AI tools like TensorFlow and Keras to build deep learning models.
  • Learn how to visualize data and AI model results with libraries like Matplotlib and Seaborn.
  • Apply AI techniques in real-world scenarios such as natural language processing and computer vision.

Topics for this course

Total learning: 20 Lessons Time: 60h 00m

What is data science
ML vs AI vs DS
Installing required Tools
What is importance of Data
Future of AI

Python Programming Overview
Var, Datatype and Operators
Conditions & Loops with break statements
functions, Regular expression and error handling
OOPS concepts, Modules and libraries
Numpy, Pandas, Matplotlib
Machine learning overview
Type of machine learning
Basic terminologies: Dataset, Training, Testing, Overfitting, Underfitting, etc.
SeaBorn visualizations & Scikit learn
Supervised Learning vs unsupervised Learning
Regressions, decision tree, random forests
Support Vector Machines (SVM), K-Nearest Neighbors (KNN) & Model evaluation
Clustering: K-means, Hierarchical Clustering
Dimensionality Reduction: PCA (Principal Component Analysis)
Neural Networks and Deep Learning
Hands-on with TensorFlow and Keras
Q-Learning and Deep Q Networks(Reinforcement)

Model Evaluation and Tuning
Mysql Basics
Statistics for data Science
Types of AI: Narrow AI (Weak AI) and General AI (Strong AI)
AI is used in various industries like healthcare, finance, entertainment, education, and more.
Natural Language Processing (NLP)
Computer Vision
Genrative AI concepts
AWS, Git, GitHub
Final projects

About the instructors

Codingsthan
4.9 ratings (200)

We are a dedicated team committed to providing top-quality education, empowering individuals with in-demand skills. Our goal is to bridge the gap between learning and real-world application through hands-on training.

20 Courses 1700 Students

Price: 19,999

Enrolled 100 Students

This Course Includes

  • Skill level : Beginner to advanced
  • Instructor : Codingsthan
  • Duration : 60 Hours
  • Lessons : 20
  • Language : English, Hindi
  • Certificate : yes

Requirements

  • No previous knowledge of coding required.
  • If you passion of learning, that's great.
  • Learn Data anytime, anywhere with your laptop or mobile