Data Science
Description
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
Features
- ✅ 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.
Target Audiences
- 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! 🔥
Requirements
- 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
Curriculum
- 5 Sections
- 30 Lessons
- 10 Weeks
Expand all sectionsCollapse all sections
- 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
FAQs
Anyone! Whether you're a student, working professional, freelancer, or career switcher, this course is designed for all skill levels. No prior coding experience is required.
The course is available in Online & Hybrid Mode, with live sessions, recorded lectures, and doubt-solving support.
No, the course starts from the basics of Python and SQL, making it beginner-friendly.
Yes! You’ll receive a Certification of Completion, which can help in job applications and freelancing.
You’ll work on real-world Data Science & Machine Learning projects using Jupyter Notebook, including:
✅ Customer Sales Analysis
✅ Sentiment Analysis on Product Reviews
✅ Stock Market Data Visualization
✅ House Price Prediction Using Regression
✅ Charts, Graphs & Histogram Analysis
Yes, we provide career guidance, freelancing tips, and job/internship assistance to help you apply your skills effectively.
You’ll have access to live doubt-solving sessions and a support community to assist you throughout the course.
Visit www.rozgarmap.com and explore the course details. Click on the enrollment section and complete the registration process. If you need assistance, you can also reach out to our support team! 🚀
Instructor
6 Students2 Courses
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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