Data Science Mentorship Program (DSMP) 1.0

WATCH FOR FREE

Instructor: Nitish SinghLanguage: Hinglish

RS - 799/- Per Month

Requirements

  • A laptop and an internet connection to attend live classes.
  •  Basic Mathematical knowledge(not much). 
  •  A zeal to learn complex topics.

About the course


CampusX Data Science Mentorship Program is a 7-month long mentorship program designed to make you an industry-ready data scientist. The core philosophy behind the design of the program is its hands-on approach. Each module under the program consists of a plethora of assignments and projects. During the course, you would be exposed to industry-relevant curriculum, tools and libraries. We would also be doing a bunch of real-life case studies to make sure you learn the concepts practically. Along with the course, we would also be focusing on interview preparation. To go with this, we will also be providing doubt support to the paid members of the course, by conducting doubt clearance classes. Apart from academics, we would also focus on portfolio building and career counselling. We strive hard to impart quality education at an affordable price and we believe we can help you in your journey to becoming a kickass data scientist. Hope to meet you in the program. Happy Learning!

After taking this course

  • You will have deep knowledge about the intricacies of data science that will help you crack jobs. 
  •  You will have knowledge of relevant tools and libraries that are being used in the industry.
  •  You will have learned to work on industry-grade projects.

Course Curriculum

Python for Data Science

  • Fundamentals of Python
  • Numpy
  • Pandas

Data Visualization

  • Basic Statistics
  • Matplotlib
  • Seaborn

SQL for Data Science

  • Database Basics
  • SQL Basics
  • Advanced SQL

Data Analysis Process 

  • Data Acquisition
  • Data Cleaning
  • Data Wrangling & EDA

Basic Machine Learning 

  • Machine Learning Theory
  • ML Metrics
  • Small End to End project

Mathematics of Data Science

  • Advanced Statistics
  • Linear Algebra
  • Probability & Calculus

Machine Learning Algorithms- 1

  • Linear & Logistics Regression 
  • SVM & KNN
  • Naive bayes  & Bagging
  • Decision Tree & Adaboost
  • Random Forest

Machine Learning Algorithms- 2

  • Gradient Boosting & XgBoost
  • PCA & K-Means
  •  Hierarchical Clustering
  • DBSCAN
  • T-sne

Practical Machine Learning - 1

  • Bias Variance Trade-off
  • Regularization 
  • Cross Validation
  • Working with Missing Data
  • Feature Scaling & Encoding

Practical Machine Learning - 2

  • Feature Transformation
  • Pipelines 
  • Date and Time
  • Feature Construction
  • Feature Selection

Practical Machine Learning - 3

  • Model Tuning
  • Imbalanced Datasets
  • Multicollinearity
  • Data Leakage
  • Working with large dataset

Model Productionalization & Deployment

End-to-End Case Studies

+ Many More

Who is this course for

01.

Industry professionals targeting to enter Data Science

02.

Students trying to make a career in Data Science

03.

High School students who are passionate about Learning Data Science

04.

Individuals with career gaps looking for a pivot in their career

What You will Learn

Python and SQL

Data Science

Data Visualization 

Feature Engineering

Model Deployment and monitoring

Machine Learning Algorithms

Working on Real-life projects

Exploratory Data Analysis


Contact Us

For any assistance  - nitish.campusx@gmail.com

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