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Data Science Course!

Acquire a solid understanding of essential data science concepts such as data manipulation, cleaning, and preprocessing using tools like Python and R!

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3,253 students

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₹39,000 ₹78,000
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  • Course MajorData Analysis
  • Course MajorMachine Learning
  • Course MajorStatistical Modeling
  • Course MajorData Visualization
  • Course MajorBig Data
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What you'll learn

Foundational Data Skills

Acquire a solid understanding of essential data science concepts such as data manipulation, cleaning, and preprocessing using tools like Python and R.

Statistical Analysis Techniques

Learn statistical methods for data analysis, hypothesis testing, and inferential statistics to extract meaningful insights from datasets.

Machine Learning Algorithms

Explore a variety of machine learning algorithms including regression, classification, clustering, and dimensionality reduction to build predictive models and uncover patterns in data.

Data Visualization and Interpretation

Master data visualization techniques using libraries like Matplotlib and Seaborn to create clear and insightful visualizations that communicate complex data effectively.

Big Data Tools and Technologies

Familiarize yourself with big data tools and technologies such as Hadoop, Spark, and Hive for processing and analyzing large datasets efficiently.

Real-World Applications and Projects

Apply data science techniques to real-world datasets and projects, gaining hands-on experience in solving business problems, making data-driven decisions, and communicating findings effectively.

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Course Content

  • Understanding the role of data science in various industries
  • Introduction to Python programming language and its applications in data science
  • Overview of essential libraries such as NumPy, Pandas, and Matplotlib

  • Data acquisition techniques: scraping, APIs, and databases
  • Data cleaning and preprocessing: handling missing values, outliers, and duplicates
  • Exploratory Data Analysis (EDA) using descriptive statistics and visualization techniques

  • Descriptive statistics: mean, median, mode, variance, and standard deviation
  • Probability distributions and hypothesis testing techniques
  • Analysis of variance (ANOVA) and chi-square tests for categorical data

  • Overview of supervised and unsupervised learning algorithms
  • Regression analysis: linear regression, polynomial regression
  • Classification techniques: logistic regression, decision trees, and ensemble methods

  • Support Vector Machines (SVM) for classification and regression
  • Clustering algorithms: K-means, hierarchical clustering
  • Dimensionality reduction techniques: PCA, t-SNE

  • Cross-validation techniques for assessing model performance
  • Evaluation metrics: accuracy, precision, recall, F1-score
  • Overfitting and underfitting: techniques for model regularization

  • Introduction to big data concepts and challenges
  • Overview of Hadoop ecosystem: HDFS, MapReduce, and YARN
  • Introduction to Apache Spark for distributed data processing

  • Data visualization techniques using libraries like Matplotlib, Seaborn, and Plotly
  • Building interactive visualizations and dashboards
  • Effective communication of insights through data storytelling

  • Introduction to NLP and its applications
  • Text preprocessing techniques: tokenization, stemming, and lemmatization
  • Sentiment analysis, text classification, and named entity recognition

  • Fundamentals of neural networks: architecture, activation functions, and backpropagation
  • Building deep learning models using frameworks like TensorFlow and Keras
  • Applications of deep learning in image classification, object detection, and natural language processing

  • Applying data science techniques to a real-world project
  • Solving a business problem or conducting research using acquired skills
  • Presenting findings and insights to peers and stakeholders

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Nandini Patel

The Data Science Course trainer is a seasoned expert with extensive experience in the field of data science and analytics. Possessing a deep understanding of statistical analysis, machine learning algorithms, and data visualization techniques, they are adept at guiding students through the intricacies of this dynamic field. With a passion for teaching and a commitment to excellence, they create a stimulating learning environment where students can explore complex concepts with confidence. Their hands-on approach, coupled with real-world examples and projects, ensures that students not only grasp theoretical concepts but also gain practical skills essential for success in the industry. As mentors, they inspire and empower students to unleash their potential and embark on rewarding careers in data science.


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Data Science Course!
₹₹39,000 ₹78,000