Job-Guaranteed Data Science Course for Future-Ready Careers
Curriculum
● Python Programming
○ Advanced Python techniques and debugging.
○ Libraries: NumPy, Pandas, Matplotlib, Seaborn for data manipulation and visualization.
● Statistics and Probability
○ Probability distributions, Bayes Theorem, and statistical significance.
○ Hypothesis Testing (ANOVA, Chi-Square Test).
● Machine Learning
○ Supervised Learning (Linear Regression, Decision Trees, Random Forest).
○ Unsupervised Learning (Clustering, Dimensionality Reduction with PCA).
○ Model Evaluation (Confusion Matrix, ROC Curve).
● Deep Learning
○ Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).
○ Frameworks: TensorFlow and Keras.
● Data Visualization
○ Dashboards using Tableau and Power BI.
● Big Data
○ Introduction to Spark and Hadoop for large-scale data processing.
● Capstone Project
○ Predictive modeling for real-world datasets such as customer churn or sales forecasting.
Highlights of Our Data Science Course
Guaranteed 100%
Job Placement
80%
Hands-On Training
Internationally
Recognized Certifications
Weekday
& Weekend Batches
Dedicated
Career Coach
Real-Time
Doubt Resolution
Easy
Payment Options
Free
Study Material
Case Studies
& Projects
Professional Profile
Building Session
Programming Languages and Tools You’ll Learn in the Data Science Course
Frequently Asked Questions
What is Data Science?
What tools and languages will I learn?
What career opportunities are available after the course?
Graduates can pursue roles such as Data Scientist, Data Analyst, Machine Learning Engineer, Business Intelligence Analyst, and AI Engineer, with attractive salary packages.
Will I receive a certificate after completing the course?
Yes, you will receive an industry-recognized certificate upon successful completion, which can boost your employability and validate your data science skills.
Is prior coding experience required for this course?
No, prior coding experience is not required. The course starts with programming basics before advancing to data analysis, machine learning, and deep learning concepts.