Data Science & Machine Learning CourseDesigned for Working Professionals
Curriculum
Module 1 (8 Weeks) – Introduction to Programming
- Decision trees & control
- Binary number system
- Strings
- Arithmetic operators
- Loops
Module 2 (8 Weeks) – Programming Constructs
- Functions
- Recursions
- Pointers
- Structures
- Unions
- Dynamic Arrays
- Asymptotic notations
Module 3 (15 Weeks) – Problem Solving & CS Fundamentals
- Time Complexity
- Arrays & Strings
- Binary Search & 2 Pointers
- Recursion, Hashing & Sorting
- Bit manipulation
- Stacks, Queues & Linked Lists
- Trees, Tries, Heap & Greedy
- DP, Graphs
- DB, OS & Computer Networks
Module 4 (8 Weeks) – Statistical Analysis & Data Analytics
- Python, Jupyter, Numpy, Pandas
- Git, Linux Terminal, File I/O
- Statistics, Probability, Linear Algebra
- Distributions, Sampling, Hypothesis Testing
- Databases, SQL, Index, Partition, Schema
- Web API, Scraping, Automation, Flask
Module 5 (8 Weeks) – Data Science & Machine Learning
- EDA, Data wrangling, Feature Engineering
- Supervised & Unsupervised Models
- Ensembling
- Factor analysis
- Predictive Modeling & Forecasting
- Recommender system
Module 6 (15 Weeks) – ML Engineering – Deep Learning & Big Data
- Keras, TensorFlow, PyTorch
- Neural Networks, Computer Vision, NLP
- Reinforcement Learning
- Research Papers in Deep Learning
- Warehouse – AWS S3, HDFS, HBase, NoSQL
- Ingestion – Kafka
- Analysis – PySpark, YARN, Airflow, Hive