Data Science for Juniors

$500.00

Category:

Description

Course Learning Outcomes :-

On completion of this course, the students will be able to:

• Understand the basic concepts of ML.
• Understand how to use different python libraries in ML.
• Work with different Regression and Classification Algorithms.
• Perform syntax and semantics in ML with Python.
• Ability to design and analyse various ML algorithms.
• Apply different concepts of ML in other application areas.

The following topics will be covered in our Data Science for Juniors Training. 

Descriptive Statistics

• Measures of Central Tendency: Mean, Median, Mode
• Measures of Dispersion: Range, Interquartile Range, Standard Deviation
• Correlation Analysis: Pearson Correlation Coefficient, Spearman Correlation Coefficient
• Visualization: Boxplot, Histogram, Scatterplot

Introduction to Probability

• Conditional Probability, Bayes Theorem
• Probability Distributions: Binomial, Poisson, Normal

Introduction to Machine Learning

• Types of Machine Learning
• Machine Learning Algorithms
• Applications of Machine Learning

Preparing to run ML algorithms

• Feature Extraction and Transformation
• Model Training and Optimization
• Model Evaluation and Selection

Regression Algorithm

• Simple Linear Regression
• Multiple Linear Regression
• Polynomial Regression
• Ridge Lasso Elasticnet
• Mini Project

Classification Algorithm

• Logistic Regression
• K-NN
• SVM
• Decision Tree Classification
• Random Forest Classification
• Mini Project

Clustering Algorithm

• K-Means
• Hierarchical Clustering
• Mini Project

Natural Language Processing

• Text Preprocessing
• Tokenization
• Parsing
• Semantic Analysis
• Sentiment Analysis
• Mini Project

Major Project (Retail/Healthcare/Finance)

• Application of all the concepts to develop a project

Prerequisites:-

• Python for Junior course: Knowledge of Python is mandatory to take up this course
• The student should have good logical and reasoning skill.

Key Features:

Training Type: Online Live Interactive Session.
Experienced Faculty.
Small Groups
Duration 30 Hours
Access to Class Recordings.
Weekday / Weekend Classes.

 

Evening Schedule:

3 Days / Week
8:30 PM – 9:30 PM EST
9:00 PM – 10:00 PM EST
9:30 PM – 10:30 PM EST
10:00 PM – 11:00 PM EST

 

Morning Schedule:

3 Days / Week
10:00 AM – 11:00 AM EST
10:30 AM – 11:30 AM EST
11:00 AM – 12:00 PM EST
11:30 AM – 12:30 PM EST

 

 

Please contact us, If you are looking for different schedule or need more information.

Phone : 1+ 734 418 2465

Email : info@learntek.org

 Inquiry Now 

USA: +1 734 418 2465 | India: +91 40 4018 1306

The Advanced Placement (AP) is a trademark registered and owned by the College Board, which is not affiliated with Learntek.org, and does not endorse this product. All other trademarks and copyrights are the property of their respective owners.

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