Data Science
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Data Science with Python & SQL – Unlock the Power of Data! 🚀
🔹 Transform Raw Data into Insights & Predictions! Master the essentials of Data Science with Python & SQL, the two most powerful tools for data analytics, visualization, and machine learning. This course is designed to take you from beginner to pro, helping you build real-world projects and gain industry-ready skills.
What You’ll Learn:
✅ Python for Data Science: Learn programming fundamentals, data structures, and automation.
✅ SQL for Data Analysis: Master database queries, joins, and data manipulation.
✅ Data Visualization: Create stunning charts with Matplotlib, Seaborn & Plotly.
✅ Machine Learning Basics: Understand predictive modeling, classification & regression.
✅ Hands-on Projects: Work on real-world datasets like stock market trends, product reviews, and more!
Why Choose This Course?
🚀 Beginner-Friendly & Industry-Focused
🖥️ 100% Practical Learning with Real-World Case Studies
🏅 Certification of Completion & Career Guidance
💡 Live Doubt-Solving & Community Support
- ✅ Comprehensive Learning: Covers Python, SQL, Data Analysis, Visualization & Machine Learning in-depth.
- ✅ Hands-on Projects: Real-world datasets like Stock Market Trends, Product Reviews, House Price Prediction & More!
- ✅ Beginner to Pro: Designed for students, professionals & career switchers – No prior coding experience needed!
- ✅ Live Doubt-Solving: Interactive Q&A sessions to clarify concepts and boost understanding.
- ✅ Industry-Relevant Skills: Practical knowledge that helps in freelancing, job placements & internships.
- ✅ Certification of Completion: Showcase your expertise with a recognized certificate.
- ✅ Flexible Learning: Online & Hybrid Mode with recorded sessions for revision.
- ✅ Career Guidance & Support: Resume building, freelancing tips, and job assistance.
- This Data Science with Python & SQL course is ideal for:
- 👩🎓 Students & Freshers – Kickstart a career in Data Science with beginner-friendly concepts.
- 💻 IT & Software Professionals – Upgrade skills in Python, SQL, and Machine Learning.
- 📊 Business Analysts & Data Enthusiasts – Learn data-driven decision-making with hands-on projects.
- 📈 Marketing & Finance Professionals – Utilize data analytics for insights and predictions.
- 🔍 Freelancers & Job Seekers – Gain industry-relevant skills and build a strong portfolio.
- 🚀 No prior coding experience needed! Just a passion for data and learning.
- 📩 Want to become a Data Science pro? Enroll now! 🔥
- This course is designed for beginners and professionals alike. To ensure the best learning experience, here’s what you need:
- ✅ Basic Computer Knowledge – No prior coding experience required!
- ✅ Python & SQL Installation – Guidance will be provided in the course.
- ✅ Curiosity to Learn – A problem-solving mindset and eagerness to explore data!
- 💡 Bonus: If you have a basic understanding of mathematics and logical reasoning, it will be an added advantage!
Curriculum
- 5 Sections
- 30 Lessons
- 10 Weeks
- Module 1: Python for Data Science8
- 1.1Chapter 1: Python Installation & Setup45 Minutes
- 1.2Chapter 2: Basic Syntax & Data Types45 Minutes
- 1.3Chapter 3: Operators in Python45 Minutes
- 1.4Chapter 4: Data Structures – Strings, Lists, Tuples, Sets & Dictionaries45 Minutes
- 1.5Chapter 5: Conditional Statements & Loops45 Minutes
- 1.6Chapter 6: Functions, Lambda Functions & Modules45 Minutes
- 1.7Chapter 7: Exception Handling & File Handling45 Minutes
- 1.8Chapter 8: Hands-on Mini Project45 Minutes
- Module 2: Data Analysis & SQL5
- 2.1Chapter 9: Introduction to NumPy: Arrays & Operations45 Minutes
- 2.2Chapter 10: Pandas: DataFrames, Data Handling & Cleaning45 Minutes
- 2.3Chapter 11: SQL Basics: Queries, Joins & Data Manipulation45 Minutes
- 2.4Chapter 12: Exploratory Data Analysis (EDA) with Pandas45 Minutes
- 2.5Chapter 13: Hands-on Data Analysis Project45 Minutes
- Module 3: Data Visualization5
- Module 4: Introduction to Machine Learning6
- 4.1Chapter 19: What is Machine Learning? Basics & Applications45 Minutes
- 4.2Chapter 20: Supervised vs. Unsupervised Learning45 Minutes
- 4.3Chapter 21: Data Preprocessing & Feature Engineering45 Minutes
- 4.4Chapter 22: Model Evaluation Metrics45 Minutes
- 4.5Chapter 23: Introduction to Regression & Classification45 Minutes
- 4.6Chapter 24: Hands-on Predictive Modeling Project45 Minutes
- Module 5: Final Projects & Career Guidance6
- 5.1Chapter 25: Customer Sales Data Analysis45 Minutes
- 5.2Chapter 26: Sentiment Analysis on Product Reviews45 Minutes
- 5.3Chapter 27: Stock Market Data Visualization45 Minutes
- 5.4Chapter 28: House Price Prediction Using Regression45 Minutes
- 5.5Chapter 29: Final Assessment & Certification45 Minutes
- 5.6Chapter 30: Career Guidance: Freelancing, Jobs & Internships45 Minutes
A passionate educator with a postgraduate degree in MCA, specializing in Python and Data Science. With 5 years of experience, I excel in Digital Marketing and Web Development. My mission is to simplify learning, empower students with industry-ready skills, and bridge the gap between knowledge and real-world application.
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