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Data Science Training Program
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15k+ interested GeeksCourse Description
Unlock the world of data science with our Data Science Certification Training Program. Explore ML, Python, Advanced Analytics, NLP, LLMs, its application in modern AI, and much more in this comprehensive course
Beginner to Advance
12 Weeks
Complete 90% Course within 90 Days & Get 90% Refund!
Extra Benefits: 1:1 Mock Interview & Job Assistance with Resume Review
In case of any queries reach us via Call/Whatsapp on: +91-9315258643
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Course Overview
Data Science stands as one of the most promising and sought-after professions in the 21st century. Its demand is skyrocketing due to a digital, programming-centric, and analytically driven field. AI-driven Data Science revolutionizes healthcare, finance, entertainment, and social media, enabling data-driven decisions and enhancing apps like ChatGPT, BERT, Midjourney, and DALL.E, making them smarter and more responsive.
Our Data Science Certification Training Program is designed to bridge the gap by equipping you with the understanding of Python, Data Analysis, Machine Learning, and Mathematics. We delve into the intricacies of Deep Learning, Natural Language Processing (NLP), and their wide-ranging applications in the modern AI industry. Our program goes beyond the technical aspects. We understand the daily challenges and pain points faced by data scientists, and we'll guide you in developing practical solutions.
Key Highlights:
- 3 months of Live Immersive Program
- Live Doubt Sessions by Industry Experts
- Master Python and its data manipulation libraries
- Explore exploratory data analysis (EDA) and data visualization
- Dive into statistical analysis and hypothesis testing
- Implement supervised learning and unsupervised learning models
- Work with classification and regression algorithms
- Dive deeper into advanced machine-learning models
- NLP and Deep Learning applications
- How AI and LLM are revolutionizing the world
- What is Prompt Engineering and ChatGPT
Projects:
- Performing Exploratory data analysis on Airbnb data.
- Predict the income of an individual based on its social and financial attributes supervised learning
- Market Basket Analysis unsupervised learning
- Working on sentiment analysis for understanding natural language processing
- Identifying hand written numbers from images - Computer Vision
- Image and voice classification Deep learning model
and many more
By enrolling in our program, you won't just gain knowledge; you'll gain insight into the real-world scenarios that data scientists navigate daily. Join us in mastering the art and science of data and AI, and empower yourself to thrive in this digital era.
Three 90 Challenge
We were listening, and we heard you loud and clear. Now get 1:1 Mock Interview & Job Assistance which includes exclusive opportunities and resume review. Register and connect with our course counselor today to learn more!
What Sets Us Apart
Project-Based Learning
Limited Batch Strength
24 X 7 Doubt Support
Recognised Certification
Expert Mentors
Hands-on, practical exercises designed to enhance your learning experience and reinforce the concepts covered in the course. These projects serve as crucial components in the learning journey, as they allow you to apply the knowledge and skills gained in real-world scenarios. Eg: Wikipedia Scraper, PubG Predictive Analysis, Spell Checker & many more.
What Sets Us Apart
Hands-on, practical exercises designed to enhance your learning experience and reinforce the concepts covered in the course. These projects serve as crucial componen
Experience personalized learning and focused attention with our limited batch strength of 55-60 candidates, ensuring optimal student-teacher interac
A dedicated service provided with this course for free to help you overcome any doubt, at any time, and anywhere. So unlea
Boost your coding street cred! Excel in the tech landscape with our comprehensive course and prestigious certificates that
With a passion for teaching, our mentor(s) sessions will provide tailored guidance to all the aspiring coders. Launch a successful tech career with
Course Content
Day 1: Introduction to Data Science and Machine Learning
- Overview of Data Science
- Fundamentals of Machine Learning
- Types of Machine Learning Algorithms
- Applications of Data Science and Machine Learning
- Introduction to Python programming language
- Setting up Python environment
- Running the first Python program
Day 2: Introduction to Python
- Basic syntax and data types in Python
- Working with variables and operators
- Using built-in functions and libraries
Day 3: Know more about Python
- Lists, tuples, and dictionaries
- Conditional statements and loops
- User-defined functions
- functions such as map, filter, lambda
Day 4: Class & OOPs Concepts
- Class & OOPs Concepts
Get recorded videos on Python for Data Science
Day 1: Data Cleaning and Preprocessing with Pandas
- Import and Exporting data
- Handling missing data
- Removing duplicates and dealing with Outliers
- Cleaning and adjustments in data
Day 2: Exploratory Data Analysis (EDA) with Pandas
- Descriptive Statistics and data summarization
- Grouping and Aggregating data
- SQL-like operation in data
Day 3: Data Visualization with Matplotlib
- Creating Basic Plots (line plots, scatter plots, histograms)
- Customizing and Styling Visualizations
- Creating Informative and Aesthetically Pleasing Visualizations
- Pair plots, Heatmaps, and Advanced Plotting technique
Day 4:Knowing about the data
- Types of analysis - univariate, multivariate analysis
- creating a hypothesis of project approach
- Introduction to statistical tests and hypothesis testing
- Implementing statistical tests in Python
Get recorded videos on Data Analysis with Python
Day 1: Final Project and Case Studies
- Participants work on a real-world data analysis project
- Applying learned Python skills to analyze and visualize data
Day 2: Feature Transformation
- Encoding
- Scaling
Day 3: Feature Reduction
- Feature Selection
- Dimetional Reduction
Day 4: Feature Balancing
- Smote, ENN, Random Sampling
Day 1: Probability and Statistics
- Basic Probability Concepts
- Random Variables
- Probability Distributions
- Statistical Inference
- Hypothesis Testing
- Regression Analysis
Day 2: Statistical Analysis with Python
- Measures of central tendency and dispersion
- Hypothesis testing and confidence intervals
- Correlation and regression analysis
- ANOVA and chi-square tests
Day 3: Supervised learning
- Classification
- Naive Bayes
Day 4: Supervised Learning
- KNN
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