Data Science
The Applied Data Science & Big Data Diploma Program, also known as the Data Science Bootcamp, is a flexible and part-time educational initiative aimed at assisting recent graduates and those looking to switch careers in entering the field of data science. This comprehensive program encompasses 26 weeks of part-time learning, followed by six months dedicated to creating a portfolio of projects. Additionally, there is a further six-month period of personalized one-on-one mentorship and job assistance post-graduation. DLytica Inc is dedicated to providing extensive support to empower learners in achieving their aspirations of a career change or kickstarting a new profession. For individuals seeking a seamless transition into the role of a data scientist, this program offers a well-structured curriculum that can be pursued alongside existing daytime commitments, making it a valuable investment in one’s professional journey.
Linear Algebra: Matrices, Vectors, Operations
Regression: Linear, Multiple Linear
Density Estimation: Probability Density, Kernel Density
Data Description: Descriptive Stats
Random Sampling: Techniques, Distribution
Parameter Estimation: Point Estimation, Confidence Intervals
Hypothesis Testing: Null/Alternative Hypotheses, p-values
1D Random Variable, Probability Distribution Function
Normal Distribution, Central Limit Theorem
Joint Probability Distribution
Python Fundamentals and Libraries: Pandas, Numpy, Matplotlib
SQL Basics, Data Structures and Algorithms
Exploratory Data Analysis, Handling Missing Values
Handling Outliers, Categorical Encoding
Normalization & Standardization, Regularization Techniques
Correlation Analysis, Forward/Backward Elimination
Univariate Selection, Random Forest Importance
Feature Selection with Decision Trees, PCA, LDA
Gradient Descent, GridSearchCV, Randomized SearchCV
Hyperparameter Tuning with Keras Tuner
XGBoost for Boosting Algorithms
Introduction to Supervised, Unsupervised, Reinforcement Learning
Linear Regression, Logistic Regression SVM, KNN, k-means Clustering
Decision Trees, Random Forest, XGBoost
Artificial Neural Networks, Convolutional Neural Networks
Recurrent Neural Networks
TensorFlow, Keras, PyTorch
Deep Neural Networks, Back propagation
Text Classification, Word Vectors and Embeddings
Recommendation Engines
Principles of Data Visualization
Matplotlib for Static Plots
Seaborn for Statistical Visualization
Plotly for Interactive Visualizations
Power BI
Introduction to Deployment and Platforms (Heroku, AWS, Azure, GCP)
Building Web Apps with Streamlit
Web Frameworks: Flask and Django
Work on real life industrial project.
Data Science Expert
Sudip Shrestha, Sushant Thapa and Anish Shilpakar are a highly experienced data scientist with a proven track record in the industry. With over 6 years of hands-on experience, he has successfully led data-driven projects, developed cutting-edge models, and provided strategic data insights across diverse sectors, making him a trusted authority in the field. Sudip , Sushant , Anish practical industry expertise is a valuable asset to our data science training programs.
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English
61h
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