Thread Rating:
  • 0 Vote(s) - 0 Average
  • 1
  • 2
  • 3
  • 4
  • 5
Data Science Course Syllabus For Beginners
#1
For beginners in data science, it's essential to start with the fundamentals and gradually build up to more advanced topics. Here's a suggested syllabus for a beginner-level data science course:
Visit Website-Best Data Science Classes in Nagpur

Week 1-2: Introduction to Data Science
Overview of Data Science and its applications
Introduction to Python programming language
Basics of data types, variables, and operators in Python
Introduction to Jupyter Notebooks for data analysis and coding exercises
Week 3-4: Data Manipulation and Analysis with Python
Introduction to libraries such as NumPy and Pandas for data manipulation
Data cleaning techniques: handling missing data, removing duplicates, etc.
Data visualization using Matplotlib and Seaborn libraries
Week 5-6: Introduction to Statistics for Data Science
Basic concepts of statistics: mean, median, mode, standard deviation, etc.
Probability theory and distributions (e.g., normal, binomial)
Statistical inference: hypothesis testing, confidence intervals
Week 7-8: Introduction to Machine Learning
Overview of machine learning concepts and types of machine learning algorithms
Supervised learning: regression and classification
Model evaluation techniques: cross-validation, confusion matrix, metrics like accuracy, precision, recall
Week 9-10: Unsupervised Learning and Dimensionality Reduction
Clustering algorithms: K-means, hierarchical clustering
Dimensionality reduction techniques: Principal Component Analysis (PCA), t-distributed Stochastic Neighbor Embedding (t-SNE)
Visit Website-Data Science Course in Nagpur
Week 11-12: Introduction to Big Data and Data Visualization
Introduction to Big Data technologies: Hadoop, Spark
Basics of SQL for querying relational databases
Advanced data visualization techniques using Plotly and interactive dashboards
Week 13-14: Real-world Data Science Projects
Working on small-scale data science projects or case studies
Applying the concepts learned throughout the course to analyze datasets and draw insights
Presenting findings and insights to peers
Week 15: Capstone Project
Collaborative capstone project where students work in teams to solve a real-world data science problem
Applying all the skills and techniques learned throughout the course
Presentation of the capstone project to instructors and peers
Additional Resources:
Online tutorials and documentation for Python, NumPy, Pandas, Matplotlib, Seaborn
Online courses and tutorials on platforms like Coursera, Udemy, and DataCamp
Books such as "Python for Data Analysis" by Wes McKinney, "An Introduction to Statistical Learning" by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
Visit Website-Data science Training in Nagpur
Reply
#2
Elevate your marketing game with our expert online marketing assignment help uk !. Our dedicated team of writers provides comprehensive assistance, ensuring your shine with brilliance. Dive into the world of strategic planning, market analysis, and consumer behavior with confidence. Explore our nursing dissertation help uk for a holistic approach to your educational journey. From essays to research papers, our skilled writers are committed to delivering excellence. Unleash your academic potential with our tailored support and propel your marketing studies to new heights. Your success is our priority!
Reply
#3
Thank you for creating such an amazing and comprehensive syllabus! It's beneficial for beginners, covering key concepts in a structured way. This will guide me through the learning process and make complex topics much easier to understand.
Reply




Users browsing this thread: 1 Guest(s)

About Ziuma

ziuma - forum diskusi dan komunitas online. disini kamu bisa berdiskusi, berbagi informasi dan membentuk komunitas secara online. Bisa juga berdiskusi dengan sesama webmaster/blogger. forum ini berbasis mybb

              Quick Links

              User Links

             powered by