Data Science and Machine Learning (Diploma)

Data handling, visualization, statistics and basic machine learning algorithms.

6 महीनेअवधि 5Chapters30टॉपिक

सिलेबस · पाठ्यक्रम

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01Unit 1: Introduction to Data Science 6 टॉपिक
  1. What is data science
  2. Data science life cycle
  3. Structured, semi-structured and unstructured data
  4. Sources of data - CSV, Excel, databases, APIs
  5. Tools - Python, Jupyter, Excel, Power BI
  6. Applications and careers
02Unit 2: Data Handling with NumPy and Pandas 6 टॉपिक
  1. NumPy arrays and operations
  2. Pandas Series and DataFrame
  3. Reading CSV and Excel files
  4. Selecting, filtering and sorting data
  5. Handling missing values and duplicates
  6. Grouping and aggregation
03Unit 3: Statistics and Visualization 6 टॉपिक
  1. Mean, median, mode
  2. Range, variance and standard deviation
  3. Correlation
  4. Normal distribution basics
  5. Line, bar, histogram, scatter and box plots
  6. Exploratory data analysis
04Unit 4: Machine Learning Fundamentals 6 टॉपिक
  1. Types of ML - supervised, unsupervised, reinforcement
  2. Features, labels, training and test sets
  3. Linear regression
  4. Logistic regression and classification
  5. k-Nearest Neighbours and decision tree
  6. k-means clustering
05Unit 5: Model Evaluation and Applications 6 टॉपिक
  1. Train-test split and cross-validation
  2. Overfitting and underfitting
  3. Confusion matrix, accuracy, precision, recall
  4. Mean squared error
  5. scikit-learn workflow
  6. Mini case study - house price or student result prediction

परिचय

आप यह कर पाएँगे

  • Explain the data science process and the role of a data analyst / data scientist
  • Load, clean and transform data using Python, NumPy and Pandas
  • Calculate and interpret descriptive statistics such as mean, median, mode and standard deviation
  • Create charts with Matplotlib / Seaborn to explore data
  • Train and evaluate basic machine learning models - linear regression, logistic regression, k-NN, decision tree, k-means
  • Use scikit-learn to split data, train models and measure accuracy, precision and recall

यह किसके लिए है

  • Diploma Computer Science & Engineering students of Semester 6 (BTEUP)
  • Diploma IT students and beginners starting a data science career

आपको क्या चाहिए

  • Python Programming (Semester 5) and school-level statistics

सवाल

Which syllabus is followed?

The BTEUP Diploma Computer Science & Engineering Semester 6 Data Science and Machine Learning syllabus. Where your college syllabus differs, the centre follows your own syllabus.

Is advanced mathematics needed?

No. Basic statistics and algebra are enough; formulas are explained with small solved examples.

Which software is used?

Python with Jupyter Notebook / Google Colab, NumPy, Pandas, Matplotlib and scikit-learn - all free.

Download the syllabus (PDF)

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